Advances in Improving Oil Recovery in Low-Permeability Hydrocarbon Resources

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 18397

Special Issue Editors


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Guest Editor
School of Earth Resources, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China
Interests: imbibition and capillary action in ideal and natural materials; multiphase flow in porous/fractured media; enhanced oil recovery; CCUS; reservoirs numerical simulation
Special Issues, Collections and Topics in MDPI journals
State Key Lab Oil & Gas Reservoir Geol & Exploita, Southwest Petroleum University, Chengdu 610500, China
Interests: chemical EOR; machine learning; CO2-EOR; unconventional reservoirs
Special Issues, Collections and Topics in MDPI journals
State Key Lab Oil & Gas Reservoir Geol & Exploita, Southwest Petroleum University, Chengdu 610500, China
Interests: enhanced oil recovery; CCUS; spontaneous imbibition; mathematical modeling; numerical simulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

At present, about 38% of the world's oil and gas are low-grade resources, mainly of low permeability, and more than 70% of China's new proven reserves are located in low-permeability reservoirs, including ultra-low-permeability reservoirs, tight reservoirs, and shale. Low-permeability reservoirs are generally characterized by low pore size, low permeability, and strong heterogeneity. The development process generally faces the problems of difficulty in energy replenishment and the limited effect of conventional secondary oil recovery methods. How to develop such oil and gas resources economically and effectively has been an important topic in the oil and gas industry. Surfactants, nanomaterials, carbon dioxide, and other new EOR media are continually used as recovery enhancement materials, and these recovery enhancement methods show great potential to solve specific problems. In addition, artificial fracturing is an efficient means of increasing seepage capacity, but water channeling through fracture systems is a threat to its economical application. Tackling the channeling problem is also an important issue during the development of such hydrocarbon resources.

This Special Issue aims to collect recent advances in new materials, new methods, and new field applications for improved oil recovery in low-permeability resources.

Topics include, but are not limited to:

  • The characterization of tight or shale formation;
  • Nonlinear seepage theory and simulation method;
  • Novel enhanced oil recovery method;
  • Multi-scale fracture system modeling;
  • The treatment of water or gas channeling.

Dr. Qingbang Meng
Dr. Bin Liang
Dr. Zhan Meng
Guest Editors

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Keywords

  • ultra-low-permeability
  • EOR
  • fracture modeling
  • channeling problem

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Published Papers (15 papers)

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Research

15 pages, 3257 KiB  
Article
Tight Oil Well Productivity Prediction Model Based on Neural Network
by Yuhang Jin, Kangliang Guo, Xinchen Gao and Qiangyu Li
Processes 2024, 12(10), 2088; https://doi.org/10.3390/pr12102088 - 26 Sep 2024
Viewed by 453
Abstract
Productivity prediction has always been an important part of reservoir development, and tight reservoirs need accurate and efficient productivity prediction models. Due to the complexity of the tight oil reservoir, the data obtained by the detection instrument need to extract data features at [...] Read more.
Productivity prediction has always been an important part of reservoir development, and tight reservoirs need accurate and efficient productivity prediction models. Due to the complexity of the tight oil reservoir, the data obtained by the detection instrument need to extract data features at a deeper level. Using the Pearson correlation coefficient and partial correlation coefficient to analyze the main control of productivity factors, eight characteristic parameters of volume coefficient, water saturation, density, effective thickness, skin factor, shale content, porosity, and effective permeability were obtained, and the specific oil production index was used as the target parameter. Two sample structures of pure static parameters and dynamic and static parameters (shale content, effective permeability, porosity, water saturation, and density as dynamic parameters, volume coefficient, skin factor, and effective thickness as static parameters) were created, and corresponding model structures (BP (Backpropagation), neural network model, and LSTM-BP (Long Short-Term Memory Backpropagation) neural network model) were designed to compare the prediction effects of models under different sample structures. The mean absolute error, root mean square error, mean relative percentage error, and coefficient of determination were used to evaluate the model results. The LSTM-BP neural network was used to predict the production capacity of the test set. The results showed that the average absolute error was 0.07, the root mean square error was 0.10, the average absolute percentage error was 21%, and the coefficient of determination was 0.97. Using wells in the WZ area for testing, the LSTM-BP model’s predictions are evenly distributed on both sides of the 45° line, separating the predicted values from actual values, with errors from the line being relatively small. In contrast, the BP model and analytical method are unable to achieve such an even distribution around the line. Experiments show that the LSTM-BP neural network model can effectively extract dynamic parameter features and has a stronger generalization ability. Full article
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14 pages, 7857 KiB  
Article
Deep Learning Framework for Accurate Static and Dynamic Prediction of CO2 Enhanced Oil Recovery and Storage Capacity
by Zhipeng Xiao, Bin Shen, Jiguang Yang, Kun Yang, Yanbin Zhang and Shenglai Yang
Processes 2024, 12(8), 1693; https://doi.org/10.3390/pr12081693 - 13 Aug 2024
Viewed by 1076
Abstract
As global warming intensifies, carbon capture, utilization, and storage (CCUS) technology is widely used to reduce greenhouse gas emissions. CO2-enhanced oil recovery (CO2-EOR) technology has, once again, received attention, which can achieve the dual benefits of oil recovery and [...] Read more.
As global warming intensifies, carbon capture, utilization, and storage (CCUS) technology is widely used to reduce greenhouse gas emissions. CO2-enhanced oil recovery (CO2-EOR) technology has, once again, received attention, which can achieve the dual benefits of oil recovery and CO2 storage. However, flexibly and effectively predicting the CO2 flooding and storage capacity of potential reservoirs is a major problem. Traditional prediction methods often lack the ability to comprehensively integrate static and dynamic predictions and, thus, cannot fully understand CO2-EOR and storage capacity. This study proposes a comprehensive deep learning framework, named LightTrans, based on a lightweight gradient boosting machine (LightGBM) and Temporal Fusion Transformers, for dynamic and static prediction of CO2-EOR and storage capacity. The model predicts cumulative oil production, CO2 storage amount, and Net Present Value on a test set with an average R-square (R2) of 0.9482 and an average mean absolute percentage error (MAPE) of 0.0143. It shows great static prediction performance. In addition, its average R2 of dynamic prediction is 0.9998, and MAPE is 0.0025. It shows excellent dynamic prediction ability. The proposed model successfully captures the time-varying characteristics of CO2-EOR and storage systems. It is worth noting that our model is 105–106 times faster than traditional numerical simulators, which once again demonstrates the high-efficiency value of the LightTrans model. Our framework provides an efficient, reliable, and intelligent solution for the development and optimization of CO2 flooding and storage. Full article
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12 pages, 4048 KiB  
Article
Research on Micropore Development Characteristics and Influencing Factors during CO2 Huff-n-Puff
by Jilun Kang, Shenglai Yang, Wei Zhang, Hong Zhang, Changsong He, Xuechun Wang, Shuangbao Wei, Kun Yang and Lilong Wang
Processes 2024, 12(8), 1665; https://doi.org/10.3390/pr12081665 - 8 Aug 2024
Viewed by 927
Abstract
CO2 huff-n-puff is an important method for the development of shale oil reservoirs. In this study, HPMI and NMR technology was used to characterize the pore distribution of the cores. The CO2 huff-n-puff experiment experiments were conducted to study the effects [...] Read more.
CO2 huff-n-puff is an important method for the development of shale oil reservoirs. In this study, HPMI and NMR technology was used to characterize the pore distribution of the cores. The CO2 huff-n-puff experiment experiments were conducted to study the effects of injection pressure, soaking time, and heterogeneity on the CO2 huff-n-puff. The results showed that the Jimsar core pores are predominantly nanopores. Mesopores with a pore radius between 2 nm and 50 nm accounted for more than 70%. CO2 huff-n-puff has been shown to effectively enhance shale oil recovery. When the injection pressure was greater than the miscible pressure, higher injection pressures were able to improve the recovery of macropores, particularly in cores with higher permeability. Appropriately extending the soaking time enhanced the diffusion of CO2 in the mesopores, and the recovery increased to above 10%. Determining the optimal soaking time is crucial to achieve maximum CO2 huff-n-puff recovery. Artificial fractures can enhance the recovery of mesopores around them, resulting in core recovery of up to 60%. However, artificial fractures exacerbate reservoir heterogeneity and reduce the CO2 huff-n-puff recovery of matrix. Increasing the cycles of CO2 huff-n-puff can effectively reduce the impact of heterogeneity on the recovery of matrix. In conclusion, expanding the area of the fracturing transformation zone and selecting the appropriate injection pressure and soaking time for the multiple cycles of CO2 huff-n-puff can effectively improve the recovery of shale oil reservoirs. Full article
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20 pages, 11299 KiB  
Article
An Accurate Calculation Method on Blasingame Production Decline Model of Horizontal Well with Dumbbell-like Hydraulic Fracture in Tight Gas Reservoirs
by Zuping Xiang, Ying Jia, Youjie Xu, Xiang Ao, Zhezhi Liu, Shijie Zhu and Zhonghua Chen
Processes 2024, 12(7), 1460; https://doi.org/10.3390/pr12071460 - 12 Jul 2024
Viewed by 799
Abstract
Blasingame production decline is an effective method to obtain permeability and single-well controlled reserves. The accurate Blasingame production decline curve needs an accurate wellbore pressure approximate solution of the real-time domain. Therefore, the aim of this study is to present a simple and [...] Read more.
Blasingame production decline is an effective method to obtain permeability and single-well controlled reserves. The accurate Blasingame production decline curve needs an accurate wellbore pressure approximate solution of the real-time domain. Therefore, the aim of this study is to present a simple and accurate wellbore pressure approximate solution and Blasingame production decline curves calculation method of a multi-stage fractured horizontal well (MFHW) with complex fractures. A semi-analytical model of MFHWs in circle-closed reservoirs is presented. The wellbore pressure and dimensionless pseudo-steady productivity index JDpss (1/bDpss) are verified with a numerical solution. The comparison result reaches a good match. Wellbore pressure and Blasingame production decline curves are used to analyze parameter sensitivity. Results show that when the crossflow from matrix to natural fracture appears after the pseudo-state flow regime, the value of the inter-porosity coefficient has an obvious influence on the pressure approximate solution of the pseudo-steady flow regime in naturally fractured gas reservoirs. The effects of relevant parameters on wellbore pressure and the Blasingame decline curve are also analyzed. The method of pseudo-steady productivity index JDpss can applied to all well and reservoir models. Full article
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18 pages, 6496 KiB  
Article
Production Feature Analysis of Global Onshore Carbonate Oil Reservoirs Based on XGBoost Classier
by Guilin Qi and Baolei Liu
Processes 2024, 12(6), 1137; https://doi.org/10.3390/pr12061137 - 31 May 2024
Cited by 1 | Viewed by 886
Abstract
Carbonate reservoirs account for 60% of global reserves for oil, making them one of the most important types of sedimentary rock reservoirs for petroleum production. This study aimed to identify key production features that significantly impact oil production rates, enhancing reservoir management and [...] Read more.
Carbonate reservoirs account for 60% of global reserves for oil, making them one of the most important types of sedimentary rock reservoirs for petroleum production. This study aimed to identify key production features that significantly impact oil production rates, enhancing reservoir management and optimizing production strategies. A comprehensive dataset is built from reserves and production history data of 377 onshore carbonate oilfields globally, encompassing features such as production, recovery rate, and recovery degree of the whole lifecycle of an oilfield. XGBoost classifier is trained by K-fold cross-validation and its hyperparameters are optimized by Optuna optimization framework. The results show that XGBoost has the best performance evaluated with metrics including accuracy, precision, recall, and F1 score comparing with decision tree, random forest, and support vector machine. Key production features are identified by analyzing the classification feature importance of XGBoost classifier, including build-up stage cumulative production, plateau stage cumulative production, plateau stage recovery rate, plateau stage recovery degrees, and peak production. In conclusion, oilfield reserve size, build-up stage cumulative production, plateau stage cumulative production, and peak production increase, while plateau stage recovery rate decreases, and the plateau stage recovery degree of small-sized oilfields is slightly greater than that of moderate and large oilfields. The research methodology of this study can serve as a reference for studying production features of other types of oil and gas reservoirs. By applying the methodology to low-permeability oilfields, this paper concludes the key production features that are as follows: low-permeability oilfields generally have lower peak recovery rate, lower plateau stage recovery rate, lower decline stage recovery degree, and lower decline stage recovery rate, along with a wide but generally lower range of decline stage cumulative production compared to conventional oilfields. Full article
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15 pages, 12951 KiB  
Article
Effect of Cross-Well Natural Fractures and Fracture Network on Production History Match and Well Location Optimization in an Ultra-Deep Gas Reservoir
by Dong Chen, Yuwei Jiao, Fenglai Yang, Chuxi Liu, Min Yang, Joseph Leines Artieda and Wei Yu
Processes 2024, 12(6), 1085; https://doi.org/10.3390/pr12061085 - 25 May 2024
Cited by 1 | Viewed by 684
Abstract
Understanding subsurface natural fracture systems is crucial to characterize well production dynamics and long-term productivity potential. In addition, the placement of future wells can benefit from in-depth fracture network connectivity investigations, vastly improving new wells’ profitability and life cycles if they are placed [...] Read more.
Understanding subsurface natural fracture systems is crucial to characterize well production dynamics and long-term productivity potential. In addition, the placement of future wells can benefit from in-depth fracture network connectivity investigations, vastly improving new wells’ profitability and life cycles if they are placed in dense, well-connected natural fracture zones. In this study, a novel natural fracture calibration workflow is proposed. This workflow starts with the extraction of sector geology and a natural fracture model from the pre-built full-field model. Then, a cross wellbore discrete fracture network (CW-DFN) is created using a novel CW-DFN generation tool, based on image log data. An innovative fracture network identification tool is developed to detect the interconnected regional fracture network (IcFN) with CW-DFN. The non-intrusive embedded discrete fracture model (EDFM) is utilized to numerically incorporate the complex IcFN and CW-DFN in a reservoir simulation, and it is history-matched by tuning their conductivities. This workflow is applied to a single vertical well within a natural fracture carbonate reservoir in Northwest China. The study results show that the number of CW-DFNs is 11, and the number of IcFNs is 72. The non-intersected natural fractures only account for 5.5% of the production, and thus can be removed to improve simulation efficiency. The history-matching absolute average relative deviation (AARD) is 15.16%. The calibrated effective fracture permeability is 280 millidarcy, with an aperture of 0.001 m, equating to a conductivity of 0.28 millidarcy-meter. The 30-year gas production forecast is estimated to be 1.66 billion cubic meters based on a history-matched model. Finally, if the well is drilled to the east of the sector, 30-year production declines to 1.33 billion cubic meters (a reduction of 20%). However, if the well is drilled to the west of the sector, 30-year production increases to 2 billion cubic meters (an improvement of 20.5%). Full article
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17 pages, 15688 KiB  
Article
Application and Analysis of Array Production Logging Technology for Multiphase Flow in Horizontal Wells
by Renwei Luo, Jianli Liu, Dong Yang and Qiao Deng
Processes 2023, 11(12), 3421; https://doi.org/10.3390/pr11123421 - 13 Dec 2023
Cited by 1 | Viewed by 1758
Abstract
Production logging (PL) instruments play a pivotal role in the comprehensive management and monitoring of oil and gas reservoirs. These devices facilitate the resolution of complex flow diagnosis challenges throughout the life cycle of hydrocarbon field exploitation. However, the advent of highly deviated [...] Read more.
Production logging (PL) instruments play a pivotal role in the comprehensive management and monitoring of oil and gas reservoirs. These devices facilitate the resolution of complex flow diagnosis challenges throughout the life cycle of hydrocarbon field exploitation. However, the advent of highly deviated well drilling technology has exposed certain limitations inherent in conventional centralized logging sensing techniques. When fluid flow within horizontal wells becomes segregated or even laminar, these traditional methods struggle to accurately decipher the zonal productions of oil, gas, and water. To address this challenge, multi-array production logging tools were developed in the late 1990s. Historically, these tools were characterized by considerable lengths, reaching up to 30 feet for an entire suite incorporating flow speed and holdup sensors that were not always collocated. Despite the integration of multiple sensors, uncertainties in determining flow profiles persisted. In this paper, we propose a novel integrated multi-parameter evaluation method based on measurements from a recently developed ultracompact flow array sensing tool, aimed at enhancing the accuracy of reservoir evaluation. The validity of the multi-parameter method is substantiated through a comparison of the new tool with an industry benchmark array PL tool on the same well. By combining the monitoring results, an optimization strategy for oil and gas extraction is presented, which is expected to improve the oil and gas recovery rate, thereby providing guidance for subsequent extraction endeavors. Moreover, we demonstrate how this innovative integrated workflow significantly enhances energy savings and efficiency, further underlining its value in modern oil and gas field management. Full article
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14 pages, 3896 KiB  
Article
Experimental Study on the Control Mechanism of Non-Equilibrium Retrograde Condensation in Buried Hill Fractured Condensate Gas Reservoirs
by Yang Liu, Yi Pan, Yang Sun and Bin Liang
Processes 2023, 11(11), 3242; https://doi.org/10.3390/pr11113242 - 17 Nov 2023
Cited by 4 | Viewed by 1063
Abstract
During the depletion development of condensate gas reservoirs, when the formation pressure drops below the dew point pressure, the condensate oil and natural gas systems are in the non-equilibrium state of foggy retrograde condensation. The rational use of the non-equilibrium phase characteristics of [...] Read more.
During the depletion development of condensate gas reservoirs, when the formation pressure drops below the dew point pressure, the condensate oil and natural gas systems are in the non-equilibrium state of foggy retrograde condensation. The rational use of the non-equilibrium phase characteristics of the foggy retrograde condensation phenomenon during the development process will be beneficial to the recovery of condensate oil and natural gas. In order to clarify the retrograde condensation control mechanism during the non-equilibrium depletion development of condensate gas reservoirs, the phase characteristics of a condensate oil and gas system were studied by constant composition expansion and constant volume depletion experiments. Then, on the basis of a long core depletion experiment and chromatographic analysis experiment, the influence of different pressure drop speeds, fluid properties, and reservoir physical properties on the control effect of non-equilibrium retrograde condensation after the coupling of the fluid retrograde condensation and reservoir core is analyzed. The results show that during the pressure decline process, the condensate oil and gas system will produce a strong foggy retrograde condensation phenomenon, with the saturation of the retrograde condensate increasing and then decreasing. The cumulative recovery of the condensate oil and natural gas, as well as the mass fraction of the heavy components in the condensate oil, increase with the increase in the depletion rate. Different fluid properties and reservoir physical properties have a great influence on the cumulative recovery degree of the condensate oil, and have little influence on the recovery degree of the natural gas. This work has a certain guiding role for the stable production and enhanced recovery of fractured condensate gas reservoirs in subsurface structures of metamorphic rocks. Full article
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19 pages, 8052 KiB  
Article
Numerical Simulation of Fracture Flow Interaction Based on Discrete Fracture Model
by Fanle Meng, Youjing Wang, Xinmin Song, Mingqiang Hao, Guosheng Qin, You Qi, Zunjing Ma and Dong Wang
Processes 2023, 11(10), 3013; https://doi.org/10.3390/pr11103013 - 19 Oct 2023
Cited by 1 | Viewed by 1390
Abstract
Hydraulic fracturing of horizontal wells is a common method for enhancing production in low-permeability and unconventional oil reservoirs. However, due to the interference between fractures, issues such as decreased production and water channeling often occur in hydraulic fracturing of horizontal wells. Therefore, studying [...] Read more.
Hydraulic fracturing of horizontal wells is a common method for enhancing production in low-permeability and unconventional oil reservoirs. However, due to the interference between fractures, issues such as decreased production and water channeling often occur in hydraulic fracturing of horizontal wells. Therefore, studying how to mitigate the effects of fracture interference is of great significance for optimizing hydraulic fracturing design and improving oil and gas recovery rates. In this paper, an oil–water two-phase discrete fracture model was established, and the grid dissection was carried out by using the optimization method to obtain a triangular grid that can finely characterize the fracture in geometry. Then, typical discrete fracture models were designed, and the influences of the fracture permeability ratio, absolute fracture scale, oil–water viscosity ratio, and fracture length on the fracture flow interference were investigated separately. The degree of fracture interference was evaluated using the fracture fractional flow rate ratio, remaining oil saturation, and sweep efficiency. This study verified fracture interaction and identified that the threshold value of the fracture permeability ratio is 9 to classify the degree of interference. Sensitivity analysis shows that the absolute size of the fracture has a significant impact on fracture interference, while the impact of the oil–water viscosity ratio and fracture length on fracture interference is relatively small. Full article
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11 pages, 4529 KiB  
Article
Investigation of the Influence of Formation Water on the Efficiency of CO2 Miscible Flooding at the Core Scale
by Yanfu Pi, Zailai Su, Li Liu, Yutong Wang, Shuai Zhang, Zhihao Li and Yufeng Zhou
Processes 2023, 11(10), 2954; https://doi.org/10.3390/pr11102954 - 12 Oct 2023
Viewed by 1260
Abstract
This study investigated the impact of formation water on the mass transfer between CO2 and crude oil in low-permeability reservoirs through CO2 miscible flooding. Formation water leads to water blocks, which affect the effectiveness of CO2 miscible flooding. Therefore, we [...] Read more.
This study investigated the impact of formation water on the mass transfer between CO2 and crude oil in low-permeability reservoirs through CO2 miscible flooding. Formation water leads to water blocks, which affect the effectiveness of CO2 miscible flooding. Therefore, we studied the impact and mechanisms of formation water on the CO2-oil miscibility. The microscale interaction between formation water-CO2-core samples was investigated using CT scanning technology to analyze its influence on core permeability parameters. In addition, CO2 miscible flooding experiments were conducted using the core displacement method to determine the effects of formation water salinity and average water saturation on minimum miscibility pressure (MMP) and oil displacement efficiency. The CT scanning results indicate that high-salinity formation water leads to a decrease in the porosity and permeability of the core as well as pore and throat sizes under miscible pressure conditions. The experimental results of CO2 miscible flooding demonstrate that CO2-oil MMP decreases as the salinity of the formation water increases. Moreover, as the average water saturation in the core increases, the water block effect strengthens, resulting in an increase in MMP. The recovery factors of cores with average water saturations of 30%, 45%, and 60% are 89.8%, 88.6%, and 87.5%, respectively, indicating that the water block effect lowers the oil displacement efficiency and miscibility. Full article
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14 pages, 5571 KiB  
Article
Mechanisms of Stress Sensitivity on Artificial Fracture Conductivity in the Flowback Stage of Shale Gas Wells
by Xuefeng Yang, Tianpeng Wu, Liming Ren, Shan Huang, Songxia Wang, Jiajun Li, Jiawei Liu, Jian Zhang, Feng Chen and Hao Chen
Processes 2023, 11(9), 2760; https://doi.org/10.3390/pr11092760 - 15 Sep 2023
Cited by 1 | Viewed by 890
Abstract
The presence of a reasonable flowback system after fracturing is a necessary condition for the high production of shale gas wells. At present, the optimization of the flowback system lacks a relevant theoretical basis. Due to this lack, this study established a new [...] Read more.
The presence of a reasonable flowback system after fracturing is a necessary condition for the high production of shale gas wells. At present, the optimization of the flowback system lacks a relevant theoretical basis. Due to this lack, this study established a new method for evaluating the conductivity of artificial fractures in shale, which can quantitatively characterize the backflow, embedment, and fragmentation of proppant during the flowback process. Then, the mechanism of the stress sensitivity of artificial fractures on fracture conductivity during the flowback stage of the shale gas well was revealed by performing the artificial fracture conductivity evaluation experiment. The results show that a large amount of proppant migrates, and the fracture conductivity decreases rapidly in the early stage of flowback, and then the decline gradually slows down. When the effective stress is low, the proppant is mainly plastically deformed, and the degree of fragmentation and embedment is low. When the effective stress exceeds 15.0 MPa, the fragmentation and embedment of the proppant will increase, and the fracture conductivity will be greatly reduced. The broken proppant ratio and embedded proppant ratio are the same under the two choke-management strategies. In the mode of increasing choke size step by step, the backflow proppant ratio is lower, and the broken proppant is mainly retained in fractures, so the damage ratio of fracture conductivity is lower. In the mode of decreasing choke size step by step, most of the proppant flows back from fractures, so the damage to fracture conductivity is greater. The research results have important theoretical guiding significance for optimizing the flowback system of shale gas wells. Full article
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20 pages, 6244 KiB  
Article
Study on SiO2 Nanofluid Alternating CO2 Enhanced Oil Recovery in Low-Permeability Sandstone Reservoirs
by Jiani Hu, Meilong Fu, Minxuan Li, Honglin He, Baofeng Hou, Lifeng Chen and Wenbo Liu
Processes 2023, 11(9), 2758; https://doi.org/10.3390/pr11092758 - 15 Sep 2023
Viewed by 1512
Abstract
Water alternating gas (WAG) flooding is a widely employed enhanced oil recovery method in various reservoirs worldwide. In this research, we will employ SiO2 nanofluid alternating with the CO2 injection method as a replacement for the conventional WAG process in oil [...] Read more.
Water alternating gas (WAG) flooding is a widely employed enhanced oil recovery method in various reservoirs worldwide. In this research, we will employ SiO2 nanofluid alternating with the CO2 injection method as a replacement for the conventional WAG process in oil flooding experiments. The conventional WAG method suffers from limitations in certain industrial applications, such as extended cycle times, susceptibility to water condensation and agglomeration, and ineffectiveness in low-permeability oil reservoirs, thus impeding the oil recovery factor. In order to solve these problems, this study introduces SiO2 nanofluid as a substitute medium and proposes a SiO2 nanofluid alternate CO2 flooding method to enhance oil recovery. Through the microcharacterization of SiO2 nanofluids, comprehensive evaluations of particle size, dispersibility, and emulsification performance were conducted. The experimental results revealed that both SiO2-I and SiO2-II nanoparticles exhibited uniform spherical morphology, with particle sizes measuring 10–20 nm and 50–60 nm, respectively. The SiO2 nanofluid formulations demonstrated excellent stability and emulsification properties, highlighting their potential utility in petroleum-related applications. Compared with other conventional oil flooding methods, the nanofluid alternating CO2 flooding effect is better, and the oil flooding effect of smaller nanoparticles is the best. Nanofluids exhibit wetting modification effects on sandstone surfaces, transforming their surface wettability from oil-wet to water-wet. This alteration reduces adhesion forces and enhances oil mobility, thereby facilitating improved fluid flow in the rock matrix. In the oil flooding experiments with different slug sizes, smaller gas and water slug sizes can delay the breakthrough time of nanofluids and CO2, thereby enhancing the effectiveness of nanofluid alternate CO2 flooding for EOR. Among them, a slug size of 0.1 PV approaches optimal performance, and further reducing the slug size has limited impact on improving the development efficiency. In oil flooding experiments with different slug ratios, the optimal slug ratio is found to be 1:1. Additionally, in oil flooding experiments using rock cores with varying permeability, lower permeability rock cores demonstrate higher oil recovery rates. Full article
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16 pages, 6765 KiB  
Article
Evaluation of Supramolecular Gel Properties and Its Application in Drilling Fluid Plugging
by Xiaoyong Du, Shaobo Feng, Haiying Lu, Yingrui Bai and Zhiqiang Lv
Processes 2023, 11(9), 2749; https://doi.org/10.3390/pr11092749 - 14 Sep 2023
Viewed by 1217
Abstract
Supramolecular gels are physically cross-linked hydrogels formed by non-covalent interactions. The synthesis, structure optimization, property regulation, and application expansion of supramolecular gels has gradually become the research hotspot in the field of gel materials. According to the non-covalent interactions such as hydrophobic association [...] Read more.
Supramolecular gels are physically cross-linked hydrogels formed by non-covalent interactions. The synthesis, structure optimization, property regulation, and application expansion of supramolecular gels has gradually become the research hotspot in the field of gel materials. According to the non-covalent interactions such as hydrophobic association and hydrogen bonding, the supramolecular gel prepared in this study has excellent rheological properties and adaptive filling and plugging properties, and can be used in the field of drilling fluid plugging. In this paper, the microstructure, rheological properties, temperature resistance, and plugging properties of supramolecular gels were studied and characterized in detail. The experimental findings demonstrated that when the strain was less than 10%, the supramolecular gel displayed an excellent linear viscoelastic region. The increase in strain weakens the rheological properties of supramolecular gel and reduces the elastic modulus of supramolecular gel to a certain extent. The supramolecular gel still had a neat three-dimensional reticular structure after curing at high temperatures, and the network of each layer was closely connected. Its extensibility and tensile properties were good, and it had excellent temperature resistance and mechanical strength. The supramolecular gel had excellent tensile and compressive properties and good deformation recovery properties. When the elongation of the supramolecular gel reached 300%, the tensile stress was 2.33 MPa. When the compression ratio of supramolecular gel was 91.2%, the compressive stress could reach 4.78 MPa. The supramolecular gel could show an excellent plugging effect on complex loss layers with different fracture pore sizes, the plugging success rate could reach more than 90%, and the plugging layer could withstand 6.3 MPa external pressure. The smart plugging fluid prepared with supramolecular gel material could quickly form a fine barrier layer on the rock surface of the reservoir. It could effectively isolate drilling fluid from entering the reservoir and reduce the adverse effects, such as permeability reduction caused by drilling fluid entering the reservoir, so as to achieve the purpose of reservoir protection. Full article
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14 pages, 8757 KiB  
Article
Establishment and Application of a New Parameter Model for Quantitative Characterization of the Heterogeneity of Thick, Coarse-Grained Clastic Reservoirs: A Case Study of the Badaowan Formation in the Western Slope of the Mahu Depression, Junggar Basin, China
by Boyu Zhou, Xiaodong Zhao, Xuebing Ji, Xinyu Wu, Wenping Zhao and Xi Rong
Processes 2023, 11(8), 2423; https://doi.org/10.3390/pr11082423 - 11 Aug 2023
Cited by 1 | Viewed by 997
Abstract
The rock composition of thick-layer, coarse-grained clastic reservoirs is complex. There are large variations in granularity and poor selectivity. Reservoirs of thick-layer, coarse-grained clastic rocks are extremely heterogeneous. Current conventional parameters for quantitative characterization of reservoir heterogeneity, such as the calculation values of [...] Read more.
The rock composition of thick-layer, coarse-grained clastic reservoirs is complex. There are large variations in granularity and poor selectivity. Reservoirs of thick-layer, coarse-grained clastic rocks are extremely heterogeneous. Current conventional parameters for quantitative characterization of reservoir heterogeneity, such as the calculation values of the permeability variation coefficient, the permeability rush coefficient, and the permeability contrast, are unbounded, have different representation angles, and the quantification degree of the characterization method is not high. This study takes the thick layer of the coarse-clastic rock reservoir developed in the western slope of the Badaowan Formation in the Mahu Depression of the Junggar Basin as an example. Through core observation, microscopic characteristics, and analysis of laboratory data, a new quantitative characterization parameter of heterogeneity is proposed, and a reservoir interpretation parameter model is established. The results were as follows. (1) The pore development of the thick, coarse-grained clastic rock reservoir is complicated, the sorting and pore structure are poor, the reservoir heterogeneity is strong, and the permeability has double peaks. (2) We propose a new parameter to evaluate reservoir heterogeneity: the fluctuation a coefficient. This essentially compares the average permeability of two adjacent layer sites with the average permeability. The fluctuation coefficient can reflect the fluctuations in permeability, and the larger the fluctuation coefficient, the stronger the heterogeneity. In addition, it has the advantages of a clear characterization target, bounded calculation data, and the same characterization angle, etc., thereby realizing the quantitative characterization of the macro degree of reservoir heterogeneity under a unified standard. (3) This parameter was used to evaluate the reservoir heterogeneity of the Badaowan Formation in the western slope of the Mahu Depression. Most wells in the study area had a fluctuation coefficient of about 0.3, but others ranged between 0.2 and 0.6. It is concluded that the larger the fluctuation coefficient of the study area, the better the oil content because these types of reservoirs have strong heterogeneity. The fluctuation coefficient can effectively reflect the strength of the heterogeneity and can also provide a reference for further reservoir enrichment research. Full article
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Article
A Comprehensive Asset Evaluation Method for Oil and Gas Projects
by Muzhen Zhang, Ailin Jia, Zhanxiang Lei and Gang Lei
Processes 2023, 11(8), 2398; https://doi.org/10.3390/pr11082398 - 9 Aug 2023
Cited by 1 | Viewed by 2205
Abstract
The rapid and accurate evaluation of oil and gas assets, specifically for new development projects, poses a significant challenge due to the various project types, limited data availability, brief periods for assessment and decision making, and constraints arising from varying contractual and taxation [...] Read more.
The rapid and accurate evaluation of oil and gas assets, specifically for new development projects, poses a significant challenge due to the various project types, limited data availability, brief periods for assessment and decision making, and constraints arising from varying contractual and taxation conditions, political stability, and societal factors. This study leverages the grading standards of the evaluation index system for new oil and gas field development projects, along with relevant mathematical theories and methods for project evaluation and optimization. We developed an asset evaluation approach for new oil and gas projects by analyzing the assets of six new oil and gas field development projects in Brazil. This analysis resulted in the grading and ranking of new projects, and we tested and demonstrated four asset optimization techniques. After a comparative analysis with conventional evaluation results, we established an oil and gas project asset optimization approach centered on the cloud model comprehensive evaluation and linear weighted ranking, exhibiting Kendall’s tau coefficient of 0.8667 with conventional methods. The findings suggest that the combination of the cloud model comprehensive evaluation method with the linear weighted ranking method can facilitate asset optimization for oil and gas field development projects, meeting the practical needs for fast selection among various new projects. Furthermore, this research offers a technical and theoretical foundation for rapid evaluation and decision making regarding new assets. Full article
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