TECHNICAL PROGRAMME | Primary Energy Supply – Future Pathways
New Exploration & Production Technologies to Extend Supply
Forum 3 | Digital Poster Plaza 1
29
April
11:30
13:30
UTC+3
New exploration and production technologies are revolutionising the oil and gas industry, enabling access to previously untapped resources, improving efficiency, and reducing the environmental impact of exploration and production activities. By leveraging these advancements, the industry can extend the supply of hydrocarbons while addressing environmental and sustainability concerns.
As Aramco expands its refining business, there is a need to customize catalysts to tackle the specific challenges these refineries are facing and improve their efficiencies. With that mission in mind, R&D team has co-developed a series of hydrocracking catalysts over the last decade, through innovation and collaboration. The innovation starts with a novel Ti/Zr-USY with unique acidity and mesoporosity. By combining the novel zeolite with advanced supports and metal preparation techniques, the hydrocracking catalysts exhibit strong performance in commercial applications, which was demonstrated by six deployments in Aramco refineries within the last decade. In one example, Riyadh Refinery adopted one such catalyst, CAN-HC15, in its hydrocracker to deal with elevated levels of demetallized oil (DMO) in the feed. DMO has significantly higher levels of organic nitrogen and heavy components compared with mainstream vacuum gas oil (VGO) feed; therefore, the feed properties impart huge challenges to the catalyst with respect to activity and stability. The new catalyst system was able to improve middle distillates yield and reduce light gas formation whilst processing almost 4 vol.% more DMO in the feed. In this presentation, we will share the journey of such innovation, the field performance of these catalysts and the future plan.
Objectives/Scope:
This study aims to develop a simple and precise method for exploring hydrocarbon deposits and monitoring underground gas content by screening vapors produced through subsurface microseepage. By analyzing the content and composition of volatile organic compounds (VOCs), we seek to identify markers indicative of oil and gas fields.
Methods, Procedures, Process:
We fabricated three types of sensors utilizing specific porous carbon sorbents—carbon nanotubes, engineered activated carbon, and commercial activated carbon-based sorbent. These sensors were deployed in an exploration field for one month to adsorb VOCs from subsurface microseepage. Subsequent thermal desorption and high-resolution comprehensive two-dimensional gas chromatography-mass spectrometry (HR-GCxGC-MS) analyses enabled detailed separation and identification of the complex analyte mixtures.
Results, Observations, Conclusions:
Among various tested porous carbon nanomaterials, activated carbons, and porous polymers, three top-performing materials were selected for sensor development. Laboratory evaluations demonstrated that the optimal sensors could adsorb and detect over 130 volatile compounds from natural oil samples in microseeps. Field deployments revealed that these sensors accumulated and identified more than 300 VOC markers, including alkanes, alkenes, alicyclic and aromatic hydrocarbons, esters, and N,S,O-heteroatom-containing organic derivatives. HR-GCxGC-MS analyses distinguished biogenic contaminants, anthropogenic compounds, and authentic markers of subsurface hydrocarbon deposits. Comparative chromatographic analyses across exploration sites facilitated the identification of critical zones containing primary oilfield deposit markers. Hierarchical clustering of the GC-MS data enabled grouping of exploration spots based on VOC profiles, aiding in the prediction of potential oil-bearing sites.
Novel/Additive Information:
This study introduces a novel workflow that combines custom sensor-based accumulation of hydrocarbon VOC markers with high-resolution GCxGC-MS analysis. This approach enhances the detection of prospective drilling sites, thereby contributing valuable insights to the field of geochemical exploration.
Co-author/s:
Maxim Orlov, Program Director, Aramco Innovations LLC - Aramco Research Center – Moscow.
Roman Borisov, Senior Scientist, TIPS RAS.
Dr. Ibrahim Atwah, Lead Geologist, Saudi Arabian Oil Company.
This study aims to develop a simple and precise method for exploring hydrocarbon deposits and monitoring underground gas content by screening vapors produced through subsurface microseepage. By analyzing the content and composition of volatile organic compounds (VOCs), we seek to identify markers indicative of oil and gas fields.
Methods, Procedures, Process:
We fabricated three types of sensors utilizing specific porous carbon sorbents—carbon nanotubes, engineered activated carbon, and commercial activated carbon-based sorbent. These sensors were deployed in an exploration field for one month to adsorb VOCs from subsurface microseepage. Subsequent thermal desorption and high-resolution comprehensive two-dimensional gas chromatography-mass spectrometry (HR-GCxGC-MS) analyses enabled detailed separation and identification of the complex analyte mixtures.
Results, Observations, Conclusions:
Among various tested porous carbon nanomaterials, activated carbons, and porous polymers, three top-performing materials were selected for sensor development. Laboratory evaluations demonstrated that the optimal sensors could adsorb and detect over 130 volatile compounds from natural oil samples in microseeps. Field deployments revealed that these sensors accumulated and identified more than 300 VOC markers, including alkanes, alkenes, alicyclic and aromatic hydrocarbons, esters, and N,S,O-heteroatom-containing organic derivatives. HR-GCxGC-MS analyses distinguished biogenic contaminants, anthropogenic compounds, and authentic markers of subsurface hydrocarbon deposits. Comparative chromatographic analyses across exploration sites facilitated the identification of critical zones containing primary oilfield deposit markers. Hierarchical clustering of the GC-MS data enabled grouping of exploration spots based on VOC profiles, aiding in the prediction of potential oil-bearing sites.
Novel/Additive Information:
This study introduces a novel workflow that combines custom sensor-based accumulation of hydrocarbon VOC markers with high-resolution GCxGC-MS analysis. This approach enhances the detection of prospective drilling sites, thereby contributing valuable insights to the field of geochemical exploration.
Co-author/s:
Maxim Orlov, Program Director, Aramco Innovations LLC - Aramco Research Center – Moscow.
Roman Borisov, Senior Scientist, TIPS RAS.
Dr. Ibrahim Atwah, Lead Geologist, Saudi Arabian Oil Company.
In recent years, problems such as production decline and the increasing difficulty in maintaining stable crude oil production have emerged in Chinese mature oil fields. The development of new environmentally friendly methods and enhanced oil recovery technologies, to further exploit the remaining oil resources is a widely discussed key challenges.
Integrated surface-subsurface microbial enhanced oil recovery(ISSM-EOR) represents an iterative advancement over conventional Indigenous/Exogenous microbial enhanced oil recovery(MEOR) technology. By integrating surface-based microbial cultivation phases with in situ metabolic processes in oil reservoirs, ISSM-EOR emphasizes enhancing microbial/metabolite concentrations through surface platforms that enable real-time monitoring and simplified control. Some of the surface-based cultivation procedures can also carry out microbial degradation of the crude oil in produced fluids extracted from oil wells.
In a pilot test of ISSM-EOR in China, Bacillus subtilis fermentation was conducted using a simplified near-wellbore process at injection sites. Non-target bacterial growth was suppressed through optimized fermentation parameters under non-sterile conditions, such as elevating the temperature to 42°C. The total bacterial concentration in the simplified fermentation broth reached 109 cells/mL, with target strain dominance exceeding 90%. The surfactant concentration metabolized by Bacillus subtilis exceeded 5 g/L, only 35% lower than that achieved in industrial-scale fermentation facilities. Huff-and-puff operation at 2 oil Well yielded 12,974 barrels of incremental oil production per cycle.
In an extended application of ISSM-EOR, produced water is reinjected into injection wells, thereby integrating microbial treatment of oil-containing produced water into the surface-based process. The surface system comprises three reaction tanks: an oil-removal conditioning tank, a fermentation reactor, and a sedimentation basin. In the oil removal tank, strains of crude oil-degrading bacteria mainly consisting of Candida viswanathii were introduced to achieve the purpose of purifying water quality. Fermentation tanks are inoculated with Pseudomonas aeruginosa strains for biomass cultivation and rhamnolipid biosynthesis. To date, this technology has been deployed across 200+ wells in China's Changqing Oilfield. In a pilot block at Changqing, 9 of 14 treated wells demonstrated production increases, with cumulative incremental production reaching 40,285 barrels between 2011-2019. Key performance metrics include: natural decline rate decreased from 15.4% to 0.4%, stage-enhanced oil recovery increased by 4.2%.
ISSM-EOR is an innovative MEOR methodology developed through systematic analysis of the primary oil-displacement mechanisms in conventional indigenous/exogenous MEOR systems. This technology integrates a dedicated surface-based cultivation phase, offering enhanced technical advantages: precision-controlled bioprocess conditions, high-purity metabolite yields, environmental friendliness, low cost. These attributes demonstrate significant potential for industrial scalability, particularly in mature oilfields.
Integrated surface-subsurface microbial enhanced oil recovery(ISSM-EOR) represents an iterative advancement over conventional Indigenous/Exogenous microbial enhanced oil recovery(MEOR) technology. By integrating surface-based microbial cultivation phases with in situ metabolic processes in oil reservoirs, ISSM-EOR emphasizes enhancing microbial/metabolite concentrations through surface platforms that enable real-time monitoring and simplified control. Some of the surface-based cultivation procedures can also carry out microbial degradation of the crude oil in produced fluids extracted from oil wells.
In a pilot test of ISSM-EOR in China, Bacillus subtilis fermentation was conducted using a simplified near-wellbore process at injection sites. Non-target bacterial growth was suppressed through optimized fermentation parameters under non-sterile conditions, such as elevating the temperature to 42°C. The total bacterial concentration in the simplified fermentation broth reached 109 cells/mL, with target strain dominance exceeding 90%. The surfactant concentration metabolized by Bacillus subtilis exceeded 5 g/L, only 35% lower than that achieved in industrial-scale fermentation facilities. Huff-and-puff operation at 2 oil Well yielded 12,974 barrels of incremental oil production per cycle.
In an extended application of ISSM-EOR, produced water is reinjected into injection wells, thereby integrating microbial treatment of oil-containing produced water into the surface-based process. The surface system comprises three reaction tanks: an oil-removal conditioning tank, a fermentation reactor, and a sedimentation basin. In the oil removal tank, strains of crude oil-degrading bacteria mainly consisting of Candida viswanathii were introduced to achieve the purpose of purifying water quality. Fermentation tanks are inoculated with Pseudomonas aeruginosa strains for biomass cultivation and rhamnolipid biosynthesis. To date, this technology has been deployed across 200+ wells in China's Changqing Oilfield. In a pilot block at Changqing, 9 of 14 treated wells demonstrated production increases, with cumulative incremental production reaching 40,285 barrels between 2011-2019. Key performance metrics include: natural decline rate decreased from 15.4% to 0.4%, stage-enhanced oil recovery increased by 4.2%.
ISSM-EOR is an innovative MEOR methodology developed through systematic analysis of the primary oil-displacement mechanisms in conventional indigenous/exogenous MEOR systems. This technology integrates a dedicated surface-based cultivation phase, offering enhanced technical advantages: precision-controlled bioprocess conditions, high-purity metabolite yields, environmental friendliness, low cost. These attributes demonstrate significant potential for industrial scalability, particularly in mature oilfields.
The selection of an optimal candidate pilot area constitutes a critical and complex phase in the development plan of oil and gas fields. Pilot-scale projects are essential for mitigating reservoir uncertainties and minimizing investment risks, and the insights gained from such studies can be extrapolated to the full-scale implementation of field development. This study aims to apply a variety of geological, operational, and economic criteria to facilitate optimal decision-making among several candidate areas.
Initially, the Reservoir Similarity Index (RSI) is computed utilizing historical oil production data and oil saturation metrics. In this context, unsupervised clustering techniques—including k-means, k-medoids, c-means, as well as metaheuristic algorithms such as Genetic Algorithms, Particle Swarm Optimization, and Simulated Annealing—are employed to ascertain the centroid of the predominant cluster. Subsequently, more operational criteria—including the number of existing applicable wells, interfering wells and adjacent wells, average distances between these wells and the center of the candidate pilot area, and the average distance from facilities—are evaluated for each alternative candidate. The corresponding calculated weights of the considered criteria are equal to 4.6%, 10.63%, 22.93%, 16.70%, 1.98%, 9.6%, 2.70% and 30.85%, respectively.
Following this assessment, a decision matrix is constructed and Multi-Criteria Decision Making (MCDM) methodologies—specifically, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Analytical Hierarchy Process (AHP), and VIKOR—are applied to compute the pilot opportunity index for each area. The results indicate that the pilot opportunity index assigned via the hierarchical analysis method yields values of 11.50%, 10.46%, and 6.97%, whereas the Shannon entropy method produces indices of 11.68%, 9.80%, and 6.80% for the three highest-ranking pilot areas, respectively. Ultimately, the area with the highest score is designated as the primary candidate for pilot implementation. Moreover, prioritization strategies such as mean rank, Borda’s count, and Copeland’s method are utilized to aggregate and identify the most favorable pilot area. To meet the validation point, the representative sectors were determined by comparing the geostatic properties, e.g., rock porosity and permeability distributions and dynamic performance between each pilot area and entire field based on simulation outputs, e.g., water cut and oil recovery factor. Finally the high computational load field scale simulation results verify and confirm the obtained results from this AI-based pilot study. Hence, this novel systematic decision making tool are proposed to utilize in enhanced oil recovery field development purposes.
Co-author/s:
Hossein Kheirollahi, Researcher, Sahnad University of Technology.
Mohammad Simjo, Associate Professor, Sahand University of Technology.
Initially, the Reservoir Similarity Index (RSI) is computed utilizing historical oil production data and oil saturation metrics. In this context, unsupervised clustering techniques—including k-means, k-medoids, c-means, as well as metaheuristic algorithms such as Genetic Algorithms, Particle Swarm Optimization, and Simulated Annealing—are employed to ascertain the centroid of the predominant cluster. Subsequently, more operational criteria—including the number of existing applicable wells, interfering wells and adjacent wells, average distances between these wells and the center of the candidate pilot area, and the average distance from facilities—are evaluated for each alternative candidate. The corresponding calculated weights of the considered criteria are equal to 4.6%, 10.63%, 22.93%, 16.70%, 1.98%, 9.6%, 2.70% and 30.85%, respectively.
Following this assessment, a decision matrix is constructed and Multi-Criteria Decision Making (MCDM) methodologies—specifically, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Analytical Hierarchy Process (AHP), and VIKOR—are applied to compute the pilot opportunity index for each area. The results indicate that the pilot opportunity index assigned via the hierarchical analysis method yields values of 11.50%, 10.46%, and 6.97%, whereas the Shannon entropy method produces indices of 11.68%, 9.80%, and 6.80% for the three highest-ranking pilot areas, respectively. Ultimately, the area with the highest score is designated as the primary candidate for pilot implementation. Moreover, prioritization strategies such as mean rank, Borda’s count, and Copeland’s method are utilized to aggregate and identify the most favorable pilot area. To meet the validation point, the representative sectors were determined by comparing the geostatic properties, e.g., rock porosity and permeability distributions and dynamic performance between each pilot area and entire field based on simulation outputs, e.g., water cut and oil recovery factor. Finally the high computational load field scale simulation results verify and confirm the obtained results from this AI-based pilot study. Hence, this novel systematic decision making tool are proposed to utilize in enhanced oil recovery field development purposes.
Co-author/s:
Hossein Kheirollahi, Researcher, Sahnad University of Technology.
Mohammad Simjo, Associate Professor, Sahand University of Technology.
The widespread use of non-biodegradable chemical additives in drilling fluids continues to pose serious environmental concerns, particularly regarding waste disposal and the risk of freshwater contamination. As the oil and gas industry transitions toward more sustainable practices, there is growing interest in identifying eco-friendly, cost-effective alternatives that meet both environmental and technical performance requirements.
This study investigates the potential of biodegradable food waste derivatives including Potato Peel Powder (PPP), Banana Peel Powder (BPP), and Gum Arabic Powder (GAP) as additives in water-based drilling fluids to improve rheological and filtration properties. Laboratory tests were conducted according to API standard procedures using a viscometer and filter press to evaluate the impact of these additives on plastic viscosity (PV), API fluid loss, and mud cake characteristics.
The results indicate that PPP and BPP significantly enhanced fluid loss control by 78% and 43%, respectively, positioning them as promising natural alternatives to synthetic fluid loss agents. Additionally, PPP and GAP improved plastic viscosity by 38% and 25%, respectively demonstrating their effectiveness in increasing carrying capacity and optimizing hole cleaning during high-viscosity sweeps.
Beyond technical performance, these bio-additives offer substantial operational and economic advantages. They are locally available, inexpensive, and derived from agricultural waste, thus supporting circular economy principles. Their use reduces reliance on costly imported chemicals, minimizes environmental impact, and aligns with sustainability goals in upstream operations. Moreover, adopting such biodegradable solutions could facilitate drilling in environmentally sensitive areas, extend the viability of mature fields, and enhance stakeholder acceptance of exploration activities.
This work underscores the feasibility and benefits of integrating biodegradable, food waste-derived materials into drilling fluid systems as part of a broader strategy for sustainable petroleum engineering practices.
This study investigates the potential of biodegradable food waste derivatives including Potato Peel Powder (PPP), Banana Peel Powder (BPP), and Gum Arabic Powder (GAP) as additives in water-based drilling fluids to improve rheological and filtration properties. Laboratory tests were conducted according to API standard procedures using a viscometer and filter press to evaluate the impact of these additives on plastic viscosity (PV), API fluid loss, and mud cake characteristics.
The results indicate that PPP and BPP significantly enhanced fluid loss control by 78% and 43%, respectively, positioning them as promising natural alternatives to synthetic fluid loss agents. Additionally, PPP and GAP improved plastic viscosity by 38% and 25%, respectively demonstrating their effectiveness in increasing carrying capacity and optimizing hole cleaning during high-viscosity sweeps.
Beyond technical performance, these bio-additives offer substantial operational and economic advantages. They are locally available, inexpensive, and derived from agricultural waste, thus supporting circular economy principles. Their use reduces reliance on costly imported chemicals, minimizes environmental impact, and aligns with sustainability goals in upstream operations. Moreover, adopting such biodegradable solutions could facilitate drilling in environmentally sensitive areas, extend the viability of mature fields, and enhance stakeholder acceptance of exploration activities.
This work underscores the feasibility and benefits of integrating biodegradable, food waste-derived materials into drilling fluid systems as part of a broader strategy for sustainable petroleum engineering practices.
While conventional hydraulic fracturing is a key technology for unlocking unconventional oil and gas resources, it faces significant challenges related to extensive water consumption and potential environmental contamination. As a promising sustainable alternative, CO₂-Energized Hydraulic Fracturing (CO₂-EHF) has seen increasing application in China's unconventional reservoirs. This technique, involving the co-injection of CO₂ with water-based fluids, creates complex fracture networks in tight media and offers multiple advantages, including enhanced hydrocarbon recovery, a 20-50% reduction in water usage, and simultaneous geological carbon sequestration.
This study presents a systematic investigation of CO2-EHF, including its fracturing mechanisms, fluid system development, operational design and field trials. We conducted experimental studies to analyze fracture propagation and proppant transport behaviors. A novel fracturing fluid system was developed by evaluating the influence of various polymer functional groups on critical fluid properties such as friction reduction, CO2 solubility, and viscosity. Furthermore, a new operational design methodology was established based on a multi-physics coupled numerical model. The effectiveness of the proposed model and fluid system was successfully validated through field trials in three wells in the Ordos Basin, China.
The findings reveal that CO2 effectively exploits natural weak plane by inducing mineral dissolution, degrading rock strength, and enhancing diffusion. This results in a substantial 30-40% decrease in rock breakdown pressure and the development of complex fracture networks dominated by shear. The utilization of high-viscosity CO2 fracturing fluids improves proppant transport and placement, ensuring effective fracture support. Specifically, custom-engineered materials exhibit outstanding performance: a drag reducer reduces friction in liquid CO2 by 12.9%, while a thickener increases CO2 viscosity by up to 68 times. More importantly, the optimization algorithms successfully guided a CO2 Pre-flush Hybrid Fracturing trial in the Ordos Basin, leading to a sustained production increase of over 37% through precise parameter adjustments, validating both the technical feasibility and economic viability of this approach.
This study pioneers a more sustainable and effective methodology for CO2 fracturing in unconventional reservoirs, significantly contributing to the advancement of a greener energy future.
Co-author/s:
Haizhu WANG, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Xianzhi SONG, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Bing WANG, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Boxin Ding, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Dr. Yaochen Zhang, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Zelong Mao, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
This study presents a systematic investigation of CO2-EHF, including its fracturing mechanisms, fluid system development, operational design and field trials. We conducted experimental studies to analyze fracture propagation and proppant transport behaviors. A novel fracturing fluid system was developed by evaluating the influence of various polymer functional groups on critical fluid properties such as friction reduction, CO2 solubility, and viscosity. Furthermore, a new operational design methodology was established based on a multi-physics coupled numerical model. The effectiveness of the proposed model and fluid system was successfully validated through field trials in three wells in the Ordos Basin, China.
The findings reveal that CO2 effectively exploits natural weak plane by inducing mineral dissolution, degrading rock strength, and enhancing diffusion. This results in a substantial 30-40% decrease in rock breakdown pressure and the development of complex fracture networks dominated by shear. The utilization of high-viscosity CO2 fracturing fluids improves proppant transport and placement, ensuring effective fracture support. Specifically, custom-engineered materials exhibit outstanding performance: a drag reducer reduces friction in liquid CO2 by 12.9%, while a thickener increases CO2 viscosity by up to 68 times. More importantly, the optimization algorithms successfully guided a CO2 Pre-flush Hybrid Fracturing trial in the Ordos Basin, leading to a sustained production increase of over 37% through precise parameter adjustments, validating both the technical feasibility and economic viability of this approach.
This study pioneers a more sustainable and effective methodology for CO2 fracturing in unconventional reservoirs, significantly contributing to the advancement of a greener energy future.
Co-author/s:
Haizhu WANG, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Xianzhi SONG, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Bing WANG, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Boxin Ding, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Dr. Yaochen Zhang, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Zelong Mao, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
This research focuses on co-optimizing natural gas storage and enhanced oil recovery in depleted gas condensate reservoirs (DGCR), which are ideal for subsurface storage sites due to their validated seal integrity. DGCRs often face challenges like pressure depletion and condensate banking, decreasing near-well permeability, and hydrocarbon recovery. The study aims to efficiently convert these reservoirs into gas storage sites, balancing market demand and improving recovery of both condensate gas and oil, thus enhancing economic viability. We develop a reservoir simulation model for converting DGCR into natural gas storage tank. During low-demand seasons (e.g., summer), natural gas is injected to restore pressure and re-vaporize condensate oil and then produced with the condensate oil during high-demand seasons (e.g., winter) to meet market demand. We further develop machine learning-based surrogate models to emulate reservoir simulation by covering a wide range of operational parameters such as well spacing, well perforation, injection and production durations, and well schedules. These models are integrated into an optimization workflow to maximize the recovery of condensate oil and condensate gas by optimizing these operational parameters. Conclusions: We successfully implemented the AI-based optimization strategy in BZ condensate gas reservoir, known for its effective interlayer sealing. Our advanced AI-based surrogate models, with a 97% accuracy, adeptly predict oil and gas recovery, considering input factors like well spacing, perforation, the duration of injection and production, and well schedules. The conversion of the BZ block into a gas storage facility was achieved by running AI-based optimization. The optimization resulted in a significant 10% increase in condensate oil recovery and a 5% rise in condensate gas recovery. Through this process, we determined optimal periods for injection (210 days) and production (150 days). Notably, we also observed considerable alleviation of the condensate banking effect near the wellbore, which substantially enhanced condensate oil productivity. This study introduces a novel method in gas storage reservoir management by transforming depleted condensate gas reservoirs into economically efficient gas storage facilities. This innovative approach, which outperforms traditional methods and conversions of dry gas reservoirs, offers dual advantages of peak regulation and enhanced oil recovery. This advancement presents a cost-effective solution for condensate gas reservoir management, representing a significant leap in reservoir engineering and practices.
Heavy oil accounts for more than 70% of crude oil resources worldwide. Considered as heavy oil main development technology, steam injection has problems such as difficulty in improving underground steam temperature, dryness and high energy consumption with large carbon emission of steam preparation on the ground. How to improve heat utilization efficiency is critical issue for heavy oil thermal recovery under the background of carbon neutrality
Herein, we propose using a reactor equipped with catalyst in the wellbore to produce a chemical reaction under the continuous supply of reactants and steam, which can generate hydrocarbon and release heat step by step towards high steam quality injection. The generation, regulation, transport, and utilization of heat-hydrocarbon sources are used as the main line. The mechanism of heat-hydrocarbon assistant steam to improve heavy oil recovery are investigated to know the demand of heat energy in different reservoir development stages. Based on this, a safe, stable and long-term multi-chemical reaction system in the complex downhole environment is constructed.
So far, the catalyst which could generate hydrocarbon and release heat under the complex underground conditions were synthesized and the effect of multi-factor such as temperature, pressure and airspeed on the conversion degree of reactant were investigated. It was found that the chemical reaction allowed the temperature of reactor to increase from 250℃ to 427℃ without steam injection and changed from 250℃ to 327℃ when steams flow through the reactor. Moreover, the product of the reaction could decrease the viscosity of heavy oil nearly 50% even at the relatively low temperature. Compare to the steam flooding, chemical reaction assist steam could further increase oil recovery factor more than 13% and significantly improve the quality of steam.
This method can solve the problem of steam injection for heavy oil production in the deeply-buried reservoir, which will provide basic theory and method guidance for the breakthrough of disruptive technology of large-scale green, low-carbon and efficient development of heavy oil.
Co-author/s:
Yiqiang Li, Professor, China University of Petroleum.
Herein, we propose using a reactor equipped with catalyst in the wellbore to produce a chemical reaction under the continuous supply of reactants and steam, which can generate hydrocarbon and release heat step by step towards high steam quality injection. The generation, regulation, transport, and utilization of heat-hydrocarbon sources are used as the main line. The mechanism of heat-hydrocarbon assistant steam to improve heavy oil recovery are investigated to know the demand of heat energy in different reservoir development stages. Based on this, a safe, stable and long-term multi-chemical reaction system in the complex downhole environment is constructed.
So far, the catalyst which could generate hydrocarbon and release heat under the complex underground conditions were synthesized and the effect of multi-factor such as temperature, pressure and airspeed on the conversion degree of reactant were investigated. It was found that the chemical reaction allowed the temperature of reactor to increase from 250℃ to 427℃ without steam injection and changed from 250℃ to 327℃ when steams flow through the reactor. Moreover, the product of the reaction could decrease the viscosity of heavy oil nearly 50% even at the relatively low temperature. Compare to the steam flooding, chemical reaction assist steam could further increase oil recovery factor more than 13% and significantly improve the quality of steam.
This method can solve the problem of steam injection for heavy oil production in the deeply-buried reservoir, which will provide basic theory and method guidance for the breakthrough of disruptive technology of large-scale green, low-carbon and efficient development of heavy oil.
Co-author/s:
Yiqiang Li, Professor, China University of Petroleum.
Integrating nanotechnology with foam-based gas injection represents a forward-looking strategy to enhance both hydrocarbon recovery efficiency and carbon storage potential in subsurface formations. This dual-purpose approach is especially relevant in carbonate reservoirs, where high heterogeneity, complex pore networks, and oil-wet rock surfaces typically limit the effectiveness of conventional EOR methods. Nanoparticle-stabilized foams have shown potential to address these challenges by improving gas mobility control, enhancing sweep efficiency, and enabling concurrent CO₂ sequestration.
This research investigates how variations in operational and fluid parameters—including nanoparticle type and concentration, gas composition (pure and hybrid gases), and injection rate—influence foam generation, stability, and propagation behavior in porous carbonate media. Special attention is given to how these factors modulate the rheological characteristics of foams, alter interfacial properties, and affect dynamic displacement behavior, including pressure drop profiles and movement of the displacement front.
The experimental phase will employ custom-designed nanofluid formulations using representative carbonate rock samples in core flooding tests. Complementary interfacial property measurements will quantify foam–rock interactions under varying temperature, pressure, and salinity conditions representative of reservoir environments. The study aims to characterize how nanoparticle–surface interactions affect foam durability, CO₂ trapping efficiency, and residual oil saturation during multiphase flow through complex pore networks.
In parallel, insights from recent advances in multiphase transport modeling and nanoparticle-enhanced interfacial science will be incorporated to support the development of mechanistic understanding and injection optimization strategies. Ultimately, this work seeks to establish a systematic framework for tailoring nanofluid-assisted gas injection processes that improve oil displacement performance while facilitating safe and reliable geological storage of CO₂.
The proposed study contributes to developing more efficient, scalable, and environmentally responsible technologies for subsurface energy applications by bridging experimental observations with engineering design principles. The outcomes are expected to support the deployment of next-generation EOR techniques that simultaneously address production efficiency and carbon management objectives—an essential step toward more sustainable hydrocarbon operations within the global energy transition.
This research investigates how variations in operational and fluid parameters—including nanoparticle type and concentration, gas composition (pure and hybrid gases), and injection rate—influence foam generation, stability, and propagation behavior in porous carbonate media. Special attention is given to how these factors modulate the rheological characteristics of foams, alter interfacial properties, and affect dynamic displacement behavior, including pressure drop profiles and movement of the displacement front.
The experimental phase will employ custom-designed nanofluid formulations using representative carbonate rock samples in core flooding tests. Complementary interfacial property measurements will quantify foam–rock interactions under varying temperature, pressure, and salinity conditions representative of reservoir environments. The study aims to characterize how nanoparticle–surface interactions affect foam durability, CO₂ trapping efficiency, and residual oil saturation during multiphase flow through complex pore networks.
In parallel, insights from recent advances in multiphase transport modeling and nanoparticle-enhanced interfacial science will be incorporated to support the development of mechanistic understanding and injection optimization strategies. Ultimately, this work seeks to establish a systematic framework for tailoring nanofluid-assisted gas injection processes that improve oil displacement performance while facilitating safe and reliable geological storage of CO₂.
The proposed study contributes to developing more efficient, scalable, and environmentally responsible technologies for subsurface energy applications by bridging experimental observations with engineering design principles. The outcomes are expected to support the deployment of next-generation EOR techniques that simultaneously address production efficiency and carbon management objectives—an essential step toward more sustainable hydrocarbon operations within the global energy transition.
Yoshiyuki Okano
Chair
General Manager, Subsurface Evaluation
Japan Petroleum Exploration Co., Ltd.
The widespread use of non-biodegradable chemical additives in drilling fluids continues to pose serious environmental concerns, particularly regarding waste disposal and the risk of freshwater contamination. As the oil and gas industry transitions toward more sustainable practices, there is growing interest in identifying eco-friendly, cost-effective alternatives that meet both environmental and technical performance requirements.
This study investigates the potential of biodegradable food waste derivatives including Potato Peel Powder (PPP), Banana Peel Powder (BPP), and Gum Arabic Powder (GAP) as additives in water-based drilling fluids to improve rheological and filtration properties. Laboratory tests were conducted according to API standard procedures using a viscometer and filter press to evaluate the impact of these additives on plastic viscosity (PV), API fluid loss, and mud cake characteristics.
The results indicate that PPP and BPP significantly enhanced fluid loss control by 78% and 43%, respectively, positioning them as promising natural alternatives to synthetic fluid loss agents. Additionally, PPP and GAP improved plastic viscosity by 38% and 25%, respectively demonstrating their effectiveness in increasing carrying capacity and optimizing hole cleaning during high-viscosity sweeps.
Beyond technical performance, these bio-additives offer substantial operational and economic advantages. They are locally available, inexpensive, and derived from agricultural waste, thus supporting circular economy principles. Their use reduces reliance on costly imported chemicals, minimizes environmental impact, and aligns with sustainability goals in upstream operations. Moreover, adopting such biodegradable solutions could facilitate drilling in environmentally sensitive areas, extend the viability of mature fields, and enhance stakeholder acceptance of exploration activities.
This work underscores the feasibility and benefits of integrating biodegradable, food waste-derived materials into drilling fluid systems as part of a broader strategy for sustainable petroleum engineering practices.
This study investigates the potential of biodegradable food waste derivatives including Potato Peel Powder (PPP), Banana Peel Powder (BPP), and Gum Arabic Powder (GAP) as additives in water-based drilling fluids to improve rheological and filtration properties. Laboratory tests were conducted according to API standard procedures using a viscometer and filter press to evaluate the impact of these additives on plastic viscosity (PV), API fluid loss, and mud cake characteristics.
The results indicate that PPP and BPP significantly enhanced fluid loss control by 78% and 43%, respectively, positioning them as promising natural alternatives to synthetic fluid loss agents. Additionally, PPP and GAP improved plastic viscosity by 38% and 25%, respectively demonstrating their effectiveness in increasing carrying capacity and optimizing hole cleaning during high-viscosity sweeps.
Beyond technical performance, these bio-additives offer substantial operational and economic advantages. They are locally available, inexpensive, and derived from agricultural waste, thus supporting circular economy principles. Their use reduces reliance on costly imported chemicals, minimizes environmental impact, and aligns with sustainability goals in upstream operations. Moreover, adopting such biodegradable solutions could facilitate drilling in environmentally sensitive areas, extend the viability of mature fields, and enhance stakeholder acceptance of exploration activities.
This work underscores the feasibility and benefits of integrating biodegradable, food waste-derived materials into drilling fluid systems as part of a broader strategy for sustainable petroleum engineering practices.
As Aramco expands its refining business, there is a need to customize catalysts to tackle the specific challenges these refineries are facing and improve their efficiencies. With that mission in mind, R&D team has co-developed a series of hydrocracking catalysts over the last decade, through innovation and collaboration. The innovation starts with a novel Ti/Zr-USY with unique acidity and mesoporosity. By combining the novel zeolite with advanced supports and metal preparation techniques, the hydrocracking catalysts exhibit strong performance in commercial applications, which was demonstrated by six deployments in Aramco refineries within the last decade. In one example, Riyadh Refinery adopted one such catalyst, CAN-HC15, in its hydrocracker to deal with elevated levels of demetallized oil (DMO) in the feed. DMO has significantly higher levels of organic nitrogen and heavy components compared with mainstream vacuum gas oil (VGO) feed; therefore, the feed properties impart huge challenges to the catalyst with respect to activity and stability. The new catalyst system was able to improve middle distillates yield and reduce light gas formation whilst processing almost 4 vol.% more DMO in the feed. In this presentation, we will share the journey of such innovation, the field performance of these catalysts and the future plan.
Mohammad Chahardowli
Speaker
Faculty member of Petroleum Engineering
Amirkabir University of Technology
The selection of an optimal candidate pilot area constitutes a critical and complex phase in the development plan of oil and gas fields. Pilot-scale projects are essential for mitigating reservoir uncertainties and minimizing investment risks, and the insights gained from such studies can be extrapolated to the full-scale implementation of field development. This study aims to apply a variety of geological, operational, and economic criteria to facilitate optimal decision-making among several candidate areas.
Initially, the Reservoir Similarity Index (RSI) is computed utilizing historical oil production data and oil saturation metrics. In this context, unsupervised clustering techniques—including k-means, k-medoids, c-means, as well as metaheuristic algorithms such as Genetic Algorithms, Particle Swarm Optimization, and Simulated Annealing—are employed to ascertain the centroid of the predominant cluster. Subsequently, more operational criteria—including the number of existing applicable wells, interfering wells and adjacent wells, average distances between these wells and the center of the candidate pilot area, and the average distance from facilities—are evaluated for each alternative candidate. The corresponding calculated weights of the considered criteria are equal to 4.6%, 10.63%, 22.93%, 16.70%, 1.98%, 9.6%, 2.70% and 30.85%, respectively.
Following this assessment, a decision matrix is constructed and Multi-Criteria Decision Making (MCDM) methodologies—specifically, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Analytical Hierarchy Process (AHP), and VIKOR—are applied to compute the pilot opportunity index for each area. The results indicate that the pilot opportunity index assigned via the hierarchical analysis method yields values of 11.50%, 10.46%, and 6.97%, whereas the Shannon entropy method produces indices of 11.68%, 9.80%, and 6.80% for the three highest-ranking pilot areas, respectively. Ultimately, the area with the highest score is designated as the primary candidate for pilot implementation. Moreover, prioritization strategies such as mean rank, Borda’s count, and Copeland’s method are utilized to aggregate and identify the most favorable pilot area. To meet the validation point, the representative sectors were determined by comparing the geostatic properties, e.g., rock porosity and permeability distributions and dynamic performance between each pilot area and entire field based on simulation outputs, e.g., water cut and oil recovery factor. Finally the high computational load field scale simulation results verify and confirm the obtained results from this AI-based pilot study. Hence, this novel systematic decision making tool are proposed to utilize in enhanced oil recovery field development purposes.
Co-author/s:
Hossein Kheirollahi, Researcher, Sahnad University of Technology.
Mohammad Simjo, Associate Professor, Sahand University of Technology.
Initially, the Reservoir Similarity Index (RSI) is computed utilizing historical oil production data and oil saturation metrics. In this context, unsupervised clustering techniques—including k-means, k-medoids, c-means, as well as metaheuristic algorithms such as Genetic Algorithms, Particle Swarm Optimization, and Simulated Annealing—are employed to ascertain the centroid of the predominant cluster. Subsequently, more operational criteria—including the number of existing applicable wells, interfering wells and adjacent wells, average distances between these wells and the center of the candidate pilot area, and the average distance from facilities—are evaluated for each alternative candidate. The corresponding calculated weights of the considered criteria are equal to 4.6%, 10.63%, 22.93%, 16.70%, 1.98%, 9.6%, 2.70% and 30.85%, respectively.
Following this assessment, a decision matrix is constructed and Multi-Criteria Decision Making (MCDM) methodologies—specifically, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Analytical Hierarchy Process (AHP), and VIKOR—are applied to compute the pilot opportunity index for each area. The results indicate that the pilot opportunity index assigned via the hierarchical analysis method yields values of 11.50%, 10.46%, and 6.97%, whereas the Shannon entropy method produces indices of 11.68%, 9.80%, and 6.80% for the three highest-ranking pilot areas, respectively. Ultimately, the area with the highest score is designated as the primary candidate for pilot implementation. Moreover, prioritization strategies such as mean rank, Borda’s count, and Copeland’s method are utilized to aggregate and identify the most favorable pilot area. To meet the validation point, the representative sectors were determined by comparing the geostatic properties, e.g., rock porosity and permeability distributions and dynamic performance between each pilot area and entire field based on simulation outputs, e.g., water cut and oil recovery factor. Finally the high computational load field scale simulation results verify and confirm the obtained results from this AI-based pilot study. Hence, this novel systematic decision making tool are proposed to utilize in enhanced oil recovery field development purposes.
Co-author/s:
Hossein Kheirollahi, Researcher, Sahnad University of Technology.
Mohammad Simjo, Associate Professor, Sahand University of Technology.
Xuhao Fan
Speaker
State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum （Beijing）, Beijing 102249, China
China University of Petroleum （Beijing）
While conventional hydraulic fracturing is a key technology for unlocking unconventional oil and gas resources, it faces significant challenges related to extensive water consumption and potential environmental contamination. As a promising sustainable alternative, CO₂-Energized Hydraulic Fracturing (CO₂-EHF) has seen increasing application in China's unconventional reservoirs. This technique, involving the co-injection of CO₂ with water-based fluids, creates complex fracture networks in tight media and offers multiple advantages, including enhanced hydrocarbon recovery, a 20-50% reduction in water usage, and simultaneous geological carbon sequestration.
This study presents a systematic investigation of CO2-EHF, including its fracturing mechanisms, fluid system development, operational design and field trials. We conducted experimental studies to analyze fracture propagation and proppant transport behaviors. A novel fracturing fluid system was developed by evaluating the influence of various polymer functional groups on critical fluid properties such as friction reduction, CO2 solubility, and viscosity. Furthermore, a new operational design methodology was established based on a multi-physics coupled numerical model. The effectiveness of the proposed model and fluid system was successfully validated through field trials in three wells in the Ordos Basin, China.
The findings reveal that CO2 effectively exploits natural weak plane by inducing mineral dissolution, degrading rock strength, and enhancing diffusion. This results in a substantial 30-40% decrease in rock breakdown pressure and the development of complex fracture networks dominated by shear. The utilization of high-viscosity CO2 fracturing fluids improves proppant transport and placement, ensuring effective fracture support. Specifically, custom-engineered materials exhibit outstanding performance: a drag reducer reduces friction in liquid CO2 by 12.9%, while a thickener increases CO2 viscosity by up to 68 times. More importantly, the optimization algorithms successfully guided a CO2 Pre-flush Hybrid Fracturing trial in the Ordos Basin, leading to a sustained production increase of over 37% through precise parameter adjustments, validating both the technical feasibility and economic viability of this approach.
This study pioneers a more sustainable and effective methodology for CO2 fracturing in unconventional reservoirs, significantly contributing to the advancement of a greener energy future.
Co-author/s:
Haizhu WANG, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Xianzhi SONG, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Bing WANG, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Boxin Ding, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Dr. Yaochen Zhang, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Zelong Mao, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
This study presents a systematic investigation of CO2-EHF, including its fracturing mechanisms, fluid system development, operational design and field trials. We conducted experimental studies to analyze fracture propagation and proppant transport behaviors. A novel fracturing fluid system was developed by evaluating the influence of various polymer functional groups on critical fluid properties such as friction reduction, CO2 solubility, and viscosity. Furthermore, a new operational design methodology was established based on a multi-physics coupled numerical model. The effectiveness of the proposed model and fluid system was successfully validated through field trials in three wells in the Ordos Basin, China.
The findings reveal that CO2 effectively exploits natural weak plane by inducing mineral dissolution, degrading rock strength, and enhancing diffusion. This results in a substantial 30-40% decrease in rock breakdown pressure and the development of complex fracture networks dominated by shear. The utilization of high-viscosity CO2 fracturing fluids improves proppant transport and placement, ensuring effective fracture support. Specifically, custom-engineered materials exhibit outstanding performance: a drag reducer reduces friction in liquid CO2 by 12.9%, while a thickener increases CO2 viscosity by up to 68 times. More importantly, the optimization algorithms successfully guided a CO2 Pre-flush Hybrid Fracturing trial in the Ordos Basin, leading to a sustained production increase of over 37% through precise parameter adjustments, validating both the technical feasibility and economic viability of this approach.
This study pioneers a more sustainable and effective methodology for CO2 fracturing in unconventional reservoirs, significantly contributing to the advancement of a greener energy future.
Co-author/s:
Haizhu WANG, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Xianzhi SONG, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Bing WANG, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Boxin Ding, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Dr. Yaochen Zhang, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Zelong Mao, State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum
Seyed Mojtaba Hosseini Nasab
Speaker
Assistant Professor
University of Science and Technology of Iran (IUST)
Integrating nanotechnology with foam-based gas injection represents a forward-looking strategy to enhance both hydrocarbon recovery efficiency and carbon storage potential in subsurface formations. This dual-purpose approach is especially relevant in carbonate reservoirs, where high heterogeneity, complex pore networks, and oil-wet rock surfaces typically limit the effectiveness of conventional EOR methods. Nanoparticle-stabilized foams have shown potential to address these challenges by improving gas mobility control, enhancing sweep efficiency, and enabling concurrent CO₂ sequestration.
This research investigates how variations in operational and fluid parameters—including nanoparticle type and concentration, gas composition (pure and hybrid gases), and injection rate—influence foam generation, stability, and propagation behavior in porous carbonate media. Special attention is given to how these factors modulate the rheological characteristics of foams, alter interfacial properties, and affect dynamic displacement behavior, including pressure drop profiles and movement of the displacement front.
The experimental phase will employ custom-designed nanofluid formulations using representative carbonate rock samples in core flooding tests. Complementary interfacial property measurements will quantify foam–rock interactions under varying temperature, pressure, and salinity conditions representative of reservoir environments. The study aims to characterize how nanoparticle–surface interactions affect foam durability, CO₂ trapping efficiency, and residual oil saturation during multiphase flow through complex pore networks.
In parallel, insights from recent advances in multiphase transport modeling and nanoparticle-enhanced interfacial science will be incorporated to support the development of mechanistic understanding and injection optimization strategies. Ultimately, this work seeks to establish a systematic framework for tailoring nanofluid-assisted gas injection processes that improve oil displacement performance while facilitating safe and reliable geological storage of CO₂.
The proposed study contributes to developing more efficient, scalable, and environmentally responsible technologies for subsurface energy applications by bridging experimental observations with engineering design principles. The outcomes are expected to support the deployment of next-generation EOR techniques that simultaneously address production efficiency and carbon management objectives—an essential step toward more sustainable hydrocarbon operations within the global energy transition.
This research investigates how variations in operational and fluid parameters—including nanoparticle type and concentration, gas composition (pure and hybrid gases), and injection rate—influence foam generation, stability, and propagation behavior in porous carbonate media. Special attention is given to how these factors modulate the rheological characteristics of foams, alter interfacial properties, and affect dynamic displacement behavior, including pressure drop profiles and movement of the displacement front.
The experimental phase will employ custom-designed nanofluid formulations using representative carbonate rock samples in core flooding tests. Complementary interfacial property measurements will quantify foam–rock interactions under varying temperature, pressure, and salinity conditions representative of reservoir environments. The study aims to characterize how nanoparticle–surface interactions affect foam durability, CO₂ trapping efficiency, and residual oil saturation during multiphase flow through complex pore networks.
In parallel, insights from recent advances in multiphase transport modeling and nanoparticle-enhanced interfacial science will be incorporated to support the development of mechanistic understanding and injection optimization strategies. Ultimately, this work seeks to establish a systematic framework for tailoring nanofluid-assisted gas injection processes that improve oil displacement performance while facilitating safe and reliable geological storage of CO₂.
The proposed study contributes to developing more efficient, scalable, and environmentally responsible technologies for subsurface energy applications by bridging experimental observations with engineering design principles. The outcomes are expected to support the deployment of next-generation EOR techniques that simultaneously address production efficiency and carbon management objectives—an essential step toward more sustainable hydrocarbon operations within the global energy transition.
Heavy oil accounts for more than 70% of crude oil resources worldwide. Considered as heavy oil main development technology, steam injection has problems such as difficulty in improving underground steam temperature, dryness and high energy consumption with large carbon emission of steam preparation on the ground. How to improve heat utilization efficiency is critical issue for heavy oil thermal recovery under the background of carbon neutrality
Herein, we propose using a reactor equipped with catalyst in the wellbore to produce a chemical reaction under the continuous supply of reactants and steam, which can generate hydrocarbon and release heat step by step towards high steam quality injection. The generation, regulation, transport, and utilization of heat-hydrocarbon sources are used as the main line. The mechanism of heat-hydrocarbon assistant steam to improve heavy oil recovery are investigated to know the demand of heat energy in different reservoir development stages. Based on this, a safe, stable and long-term multi-chemical reaction system in the complex downhole environment is constructed.
So far, the catalyst which could generate hydrocarbon and release heat under the complex underground conditions were synthesized and the effect of multi-factor such as temperature, pressure and airspeed on the conversion degree of reactant were investigated. It was found that the chemical reaction allowed the temperature of reactor to increase from 250℃ to 427℃ without steam injection and changed from 250℃ to 327℃ when steams flow through the reactor. Moreover, the product of the reaction could decrease the viscosity of heavy oil nearly 50% even at the relatively low temperature. Compare to the steam flooding, chemical reaction assist steam could further increase oil recovery factor more than 13% and significantly improve the quality of steam.
This method can solve the problem of steam injection for heavy oil production in the deeply-buried reservoir, which will provide basic theory and method guidance for the breakthrough of disruptive technology of large-scale green, low-carbon and efficient development of heavy oil.
Co-author/s:
Yiqiang Li, Professor, China University of Petroleum.
Herein, we propose using a reactor equipped with catalyst in the wellbore to produce a chemical reaction under the continuous supply of reactants and steam, which can generate hydrocarbon and release heat step by step towards high steam quality injection. The generation, regulation, transport, and utilization of heat-hydrocarbon sources are used as the main line. The mechanism of heat-hydrocarbon assistant steam to improve heavy oil recovery are investigated to know the demand of heat energy in different reservoir development stages. Based on this, a safe, stable and long-term multi-chemical reaction system in the complex downhole environment is constructed.
So far, the catalyst which could generate hydrocarbon and release heat under the complex underground conditions were synthesized and the effect of multi-factor such as temperature, pressure and airspeed on the conversion degree of reactant were investigated. It was found that the chemical reaction allowed the temperature of reactor to increase from 250℃ to 427℃ without steam injection and changed from 250℃ to 327℃ when steams flow through the reactor. Moreover, the product of the reaction could decrease the viscosity of heavy oil nearly 50% even at the relatively low temperature. Compare to the steam flooding, chemical reaction assist steam could further increase oil recovery factor more than 13% and significantly improve the quality of steam.
This method can solve the problem of steam injection for heavy oil production in the deeply-buried reservoir, which will provide basic theory and method guidance for the breakthrough of disruptive technology of large-scale green, low-carbon and efficient development of heavy oil.
Co-author/s:
Yiqiang Li, Professor, China University of Petroleum.
Lidong Mi
Speaker
Senior Engineer
Sinopec Petroleum Exploration and Production Research Institute
This research focuses on co-optimizing natural gas storage and enhanced oil recovery in depleted gas condensate reservoirs (DGCR), which are ideal for subsurface storage sites due to their validated seal integrity. DGCRs often face challenges like pressure depletion and condensate banking, decreasing near-well permeability, and hydrocarbon recovery. The study aims to efficiently convert these reservoirs into gas storage sites, balancing market demand and improving recovery of both condensate gas and oil, thus enhancing economic viability. We develop a reservoir simulation model for converting DGCR into natural gas storage tank. During low-demand seasons (e.g., summer), natural gas is injected to restore pressure and re-vaporize condensate oil and then produced with the condensate oil during high-demand seasons (e.g., winter) to meet market demand. We further develop machine learning-based surrogate models to emulate reservoir simulation by covering a wide range of operational parameters such as well spacing, well perforation, injection and production durations, and well schedules. These models are integrated into an optimization workflow to maximize the recovery of condensate oil and condensate gas by optimizing these operational parameters. Conclusions: We successfully implemented the AI-based optimization strategy in BZ condensate gas reservoir, known for its effective interlayer sealing. Our advanced AI-based surrogate models, with a 97% accuracy, adeptly predict oil and gas recovery, considering input factors like well spacing, perforation, the duration of injection and production, and well schedules. The conversion of the BZ block into a gas storage facility was achieved by running AI-based optimization. The optimization resulted in a significant 10% increase in condensate oil recovery and a 5% rise in condensate gas recovery. Through this process, we determined optimal periods for injection (210 days) and production (150 days). Notably, we also observed considerable alleviation of the condensate banking effect near the wellbore, which substantially enhanced condensate oil productivity. This study introduces a novel method in gas storage reservoir management by transforming depleted condensate gas reservoirs into economically efficient gas storage facilities. This innovative approach, which outperforms traditional methods and conversions of dry gas reservoirs, offers dual advantages of peak regulation and enhanced oil recovery. This advancement presents a cost-effective solution for condensate gas reservoir management, representing a significant leap in reservoir engineering and practices.
Objectives/Scope:
This study aims to develop a simple and precise method for exploring hydrocarbon deposits and monitoring underground gas content by screening vapors produced through subsurface microseepage. By analyzing the content and composition of volatile organic compounds (VOCs), we seek to identify markers indicative of oil and gas fields.
Methods, Procedures, Process:
We fabricated three types of sensors utilizing specific porous carbon sorbents—carbon nanotubes, engineered activated carbon, and commercial activated carbon-based sorbent. These sensors were deployed in an exploration field for one month to adsorb VOCs from subsurface microseepage. Subsequent thermal desorption and high-resolution comprehensive two-dimensional gas chromatography-mass spectrometry (HR-GCxGC-MS) analyses enabled detailed separation and identification of the complex analyte mixtures.
Results, Observations, Conclusions:
Among various tested porous carbon nanomaterials, activated carbons, and porous polymers, three top-performing materials were selected for sensor development. Laboratory evaluations demonstrated that the optimal sensors could adsorb and detect over 130 volatile compounds from natural oil samples in microseeps. Field deployments revealed that these sensors accumulated and identified more than 300 VOC markers, including alkanes, alkenes, alicyclic and aromatic hydrocarbons, esters, and N,S,O-heteroatom-containing organic derivatives. HR-GCxGC-MS analyses distinguished biogenic contaminants, anthropogenic compounds, and authentic markers of subsurface hydrocarbon deposits. Comparative chromatographic analyses across exploration sites facilitated the identification of critical zones containing primary oilfield deposit markers. Hierarchical clustering of the GC-MS data enabled grouping of exploration spots based on VOC profiles, aiding in the prediction of potential oil-bearing sites.
Novel/Additive Information:
This study introduces a novel workflow that combines custom sensor-based accumulation of hydrocarbon VOC markers with high-resolution GCxGC-MS analysis. This approach enhances the detection of prospective drilling sites, thereby contributing valuable insights to the field of geochemical exploration.
Co-author/s:
Maxim Orlov, Program Director, Aramco Innovations LLC - Aramco Research Center – Moscow.
Roman Borisov, Senior Scientist, TIPS RAS.
Dr. Ibrahim Atwah, Lead Geologist, Saudi Arabian Oil Company.
This study aims to develop a simple and precise method for exploring hydrocarbon deposits and monitoring underground gas content by screening vapors produced through subsurface microseepage. By analyzing the content and composition of volatile organic compounds (VOCs), we seek to identify markers indicative of oil and gas fields.
Methods, Procedures, Process:
We fabricated three types of sensors utilizing specific porous carbon sorbents—carbon nanotubes, engineered activated carbon, and commercial activated carbon-based sorbent. These sensors were deployed in an exploration field for one month to adsorb VOCs from subsurface microseepage. Subsequent thermal desorption and high-resolution comprehensive two-dimensional gas chromatography-mass spectrometry (HR-GCxGC-MS) analyses enabled detailed separation and identification of the complex analyte mixtures.
Results, Observations, Conclusions:
Among various tested porous carbon nanomaterials, activated carbons, and porous polymers, three top-performing materials were selected for sensor development. Laboratory evaluations demonstrated that the optimal sensors could adsorb and detect over 130 volatile compounds from natural oil samples in microseeps. Field deployments revealed that these sensors accumulated and identified more than 300 VOC markers, including alkanes, alkenes, alicyclic and aromatic hydrocarbons, esters, and N,S,O-heteroatom-containing organic derivatives. HR-GCxGC-MS analyses distinguished biogenic contaminants, anthropogenic compounds, and authentic markers of subsurface hydrocarbon deposits. Comparative chromatographic analyses across exploration sites facilitated the identification of critical zones containing primary oilfield deposit markers. Hierarchical clustering of the GC-MS data enabled grouping of exploration spots based on VOC profiles, aiding in the prediction of potential oil-bearing sites.
Novel/Additive Information:
This study introduces a novel workflow that combines custom sensor-based accumulation of hydrocarbon VOC markers with high-resolution GCxGC-MS analysis. This approach enhances the detection of prospective drilling sites, thereby contributing valuable insights to the field of geochemical exploration.
Co-author/s:
Maxim Orlov, Program Director, Aramco Innovations LLC - Aramco Research Center – Moscow.
Roman Borisov, Senior Scientist, TIPS RAS.
Dr. Ibrahim Atwah, Lead Geologist, Saudi Arabian Oil Company.
In recent years, problems such as production decline and the increasing difficulty in maintaining stable crude oil production have emerged in Chinese mature oil fields. The development of new environmentally friendly methods and enhanced oil recovery technologies, to further exploit the remaining oil resources is a widely discussed key challenges.
Integrated surface-subsurface microbial enhanced oil recovery(ISSM-EOR) represents an iterative advancement over conventional Indigenous/Exogenous microbial enhanced oil recovery(MEOR) technology. By integrating surface-based microbial cultivation phases with in situ metabolic processes in oil reservoirs, ISSM-EOR emphasizes enhancing microbial/metabolite concentrations through surface platforms that enable real-time monitoring and simplified control. Some of the surface-based cultivation procedures can also carry out microbial degradation of the crude oil in produced fluids extracted from oil wells.
In a pilot test of ISSM-EOR in China, Bacillus subtilis fermentation was conducted using a simplified near-wellbore process at injection sites. Non-target bacterial growth was suppressed through optimized fermentation parameters under non-sterile conditions, such as elevating the temperature to 42°C. The total bacterial concentration in the simplified fermentation broth reached 109 cells/mL, with target strain dominance exceeding 90%. The surfactant concentration metabolized by Bacillus subtilis exceeded 5 g/L, only 35% lower than that achieved in industrial-scale fermentation facilities. Huff-and-puff operation at 2 oil Well yielded 12,974 barrels of incremental oil production per cycle.
In an extended application of ISSM-EOR, produced water is reinjected into injection wells, thereby integrating microbial treatment of oil-containing produced water into the surface-based process. The surface system comprises three reaction tanks: an oil-removal conditioning tank, a fermentation reactor, and a sedimentation basin. In the oil removal tank, strains of crude oil-degrading bacteria mainly consisting of Candida viswanathii were introduced to achieve the purpose of purifying water quality. Fermentation tanks are inoculated with Pseudomonas aeruginosa strains for biomass cultivation and rhamnolipid biosynthesis. To date, this technology has been deployed across 200+ wells in China's Changqing Oilfield. In a pilot block at Changqing, 9 of 14 treated wells demonstrated production increases, with cumulative incremental production reaching 40,285 barrels between 2011-2019. Key performance metrics include: natural decline rate decreased from 15.4% to 0.4%, stage-enhanced oil recovery increased by 4.2%.
ISSM-EOR is an innovative MEOR methodology developed through systematic analysis of the primary oil-displacement mechanisms in conventional indigenous/exogenous MEOR systems. This technology integrates a dedicated surface-based cultivation phase, offering enhanced technical advantages: precision-controlled bioprocess conditions, high-purity metabolite yields, environmental friendliness, low cost. These attributes demonstrate significant potential for industrial scalability, particularly in mature oilfields.
Integrated surface-subsurface microbial enhanced oil recovery(ISSM-EOR) represents an iterative advancement over conventional Indigenous/Exogenous microbial enhanced oil recovery(MEOR) technology. By integrating surface-based microbial cultivation phases with in situ metabolic processes in oil reservoirs, ISSM-EOR emphasizes enhancing microbial/metabolite concentrations through surface platforms that enable real-time monitoring and simplified control. Some of the surface-based cultivation procedures can also carry out microbial degradation of the crude oil in produced fluids extracted from oil wells.
In a pilot test of ISSM-EOR in China, Bacillus subtilis fermentation was conducted using a simplified near-wellbore process at injection sites. Non-target bacterial growth was suppressed through optimized fermentation parameters under non-sterile conditions, such as elevating the temperature to 42°C. The total bacterial concentration in the simplified fermentation broth reached 109 cells/mL, with target strain dominance exceeding 90%. The surfactant concentration metabolized by Bacillus subtilis exceeded 5 g/L, only 35% lower than that achieved in industrial-scale fermentation facilities. Huff-and-puff operation at 2 oil Well yielded 12,974 barrels of incremental oil production per cycle.
In an extended application of ISSM-EOR, produced water is reinjected into injection wells, thereby integrating microbial treatment of oil-containing produced water into the surface-based process. The surface system comprises three reaction tanks: an oil-removal conditioning tank, a fermentation reactor, and a sedimentation basin. In the oil removal tank, strains of crude oil-degrading bacteria mainly consisting of Candida viswanathii were introduced to achieve the purpose of purifying water quality. Fermentation tanks are inoculated with Pseudomonas aeruginosa strains for biomass cultivation and rhamnolipid biosynthesis. To date, this technology has been deployed across 200+ wells in China's Changqing Oilfield. In a pilot block at Changqing, 9 of 14 treated wells demonstrated production increases, with cumulative incremental production reaching 40,285 barrels between 2011-2019. Key performance metrics include: natural decline rate decreased from 15.4% to 0.4%, stage-enhanced oil recovery increased by 4.2%.
ISSM-EOR is an innovative MEOR methodology developed through systematic analysis of the primary oil-displacement mechanisms in conventional indigenous/exogenous MEOR systems. This technology integrates a dedicated surface-based cultivation phase, offering enhanced technical advantages: precision-controlled bioprocess conditions, high-purity metabolite yields, environmental friendliness, low cost. These attributes demonstrate significant potential for industrial scalability, particularly in mature oilfields.
