Article
Energy & Fuels
Shijing Chen, Yang Liu, Jinchuan Zhang, Pei Li, Xuan Tang, Zhongming Li, Zhe Dong, Longfei Xu, Xingxu Zhao
Summary: The study conducted physical simulation experiments of rock fracturing and discovered four main fracture patterns within different lithologies using a self-developed simulation device and real-time monitoring system. Trends of fracture evolution and influencing factors were explored, providing insights for reservoir fracturing ability and design in unconventional reservoir development.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2021)
Article
Energy & Fuels
C. P. Zhang, P. Cheng, Z. Y. Ma, P. G. Ranjith, J. P. Zhou
Summary: The study compared the fracturing efficiency of CO2-based fracturing (CBF) and water-based fracturing (WBF) on siltstone samples, revealing that CBF has lower breakdown pressure and greater fracture aperture compared to WBF, which helps create more complex and efficient fracture networks.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2021)
Article
Engineering, Chemical
Ziqi Gao, Ning Li, Jiahui Tu, Liu Yang
Summary: This study investigated the effect of non-uniform distribution of minerals on the development of microcracks during hydraulic fracturing. The results showed that the presence of quartz could alter the propagation path of fractures and increase the width of hydraulic fractures. Additionally, the size and content of quartz influenced the morphology and development of cracks in different types of granite rocks.
Article
Energy & Fuels
Yongming Yang, Xiao Li, Zhanpeng Fu, Yang Ju
Summary: This study introduced a method for preparing artificial cores of plastic sandstones and verified their consistency with natural sandstones. The effects of in-situ horizontal stress difference (HSD) and material plasticity on the hydraulic fracture propagation in plastic sandstones were revealed. The results showed that the stronger the plasticity, the greater the breakdown pressure of sandstones. Clay minerals increased the compactness of sandstones, leading to decreased permeability and breakdown pressure in sandstones with a higher plasticity coefficient. The influence of in-situ HSD on the breakdown pressure in sandstones was not weakened by the plasticity. Plasticity significantly affected the fracture propagation morphology, with weakly plastic sandstones likely forming a flat and straight main fracture perpendicular to the wellbore, while strongly plastic sandstones were more likely to form a complex fracture surface and the propagation of fractures was considerably inhibited. Plasticity could also weaken the influence of in-situ HSD on the fracture propagation morphology. This study provides an important way to reveal the propagation mechanisms of hydraulic fractures in plastic sandstones.
GEOMECHANICS AND GEOPHYSICS FOR GEO-ENERGY AND GEO-RESOURCES
(2022)
Article
Energy & Fuels
Minghui Li, Fujian Zhou, Lishan Yuan, Liang Chen, Xiaodong Hu, Guopeng Huang, Shaobo Han
Summary: This study investigates the competitive propagation of multiple fractures in heterogeneous layered formations, revealing the impact of geological parameters on fracture pressure, fluid volume, and fracture length. The findings offer valuable insights for design of separate-layer fracturing in such formations.
Article
Energy & Fuels
Xinglong Zhao, Bingxiang Huang, Qingwang Cai, Long Zhao, Bin Chen
Summary: Pore pressure is an important factor in sandstone hydraulic fracturing experiments. The experimental results show that there is a positive correlation between breakdown pressure and pore pressure. As pore pressure increases, the energy released during fracturing and the initial rupture range also increase. The results provide a theoretical basis for unconventional oil and gas resource exploitation.
GEOMECHANICS AND GEOPHYSICS FOR GEO-ENERGY AND GEO-RESOURCES
(2023)
Article
Engineering, Geological
Egor Dontsov
Summary: The purpose of this study is to investigate the morphology of simultaneously propagating hydraulic fractures from a horizontal well. The findings show that stress interaction between the fractures affects their shapes, with different parameters having different impacts.
INTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS
(2022)
Article
Energy & Fuels
Bangtang Yin, Chao Zhang, Zhiyuan Wang, Baojiang Sun, Yonghai Gao, Xiaopeng Wang, Chuang Bi, Qilong Zhang, Jintang Wang, Juntai Shi
Summary: A method based on fractal interpolation theory was proposed to generate fractures with rough surfaces. A proppant-fracturing fluid two-phase flow model was established using computational fluid dynamics (CFD)-discrete element method (DEM) coupling considering particle-particle, particle-wall, and particle-fluid interactions. Simulation results were verified with experimental data, demonstrating the model's capability to accurately reproduce proppant transport and accumulation in rough fractures.
PETROLEUM EXPLORATION AND DEVELOPMENT
(2023)
Article
Energy & Fuels
Bo Luo, George K. Wong, Jianchun Guo, Wei Fu, Guanyi Lu, Andrew P. Bunger
Summary: Solid particulate additives are used to promote uniform growth of hydraulic fractures in horizontal oil and gas wells. This study models the propagation of multi-fractures with particle diverter-induced pressure losses. Simulation results show that a model-based optimization could improve the effectiveness of the diverter technology and promote a uniform multi-fracture growth. Rating: 6 out of 10.
GEOENERGY SCIENCE AND ENGINEERING
(2023)
Article
Geosciences, Multidisciplinary
Lei Wang, Jun Zhou, Yintong Guo, Xuehang Song, Wuhao Guo
Summary: This study investigates the effect of various factors on gas production in hydraulic fracturing of marine shale gas through laboratory experiments. Deviatoric stress, confining pressure, pumping rate, fracturing fluid viscosity, and bedding angle were considered as key parameters. The results show that factors such as deviatoric stress, confining pressure, pumping rate, and fracturing fluid viscosity affect the breakdown pressure. Geological factors have a greater influence on the breakdown pressure compared to engineering factors. The presence of natural fractures can substantially increase the total fracture length. Low deviatoric stress, low confining pressure, low viscous slick-water, and high bedding angle facilitate the activation of natural and bedding fractures, forming a complex fracture network.
FRONTIERS IN EARTH SCIENCE
(2022)
Article
Energy & Fuels
Andrea Munoz-Ibanez, Miguel Herbon-Penabad, Jordi Delgado-Martin, Leandro Alejano-Monge, Jose Alvarellos-Iglesias, Jacobo Canal-Vila
Summary: We have developed a versatile testing device for hydraulic fracturing experiments under true triaxial conditions. The device is based on a stiff biaxial frame and can accommodate large rock samples. Using a low-permeability rock, we conducted tests under different pressures and verified the applicability of fracture mechanics models. The presence of heterogeneities and defects in the rock matrix may affect the interpretation of hydrofracturing tests.
GEOMECHANICS AND GEOPHYSICS FOR GEO-ENERGY AND GEO-RESOURCES
(2023)
Article
Energy & Fuels
Rizwan Ahmed Khan, Mobeen Murtaza, Ayyaz Mustafa, Abdulazeez Abdulraheem, Mohamed Mahmoud, Muhammad Shahzad Kamal
Summary: Swelling clays in hydrocarbon-bearing rocks can cause difficulties in developing unconventional hydrocarbon reservoirs. This study investigated the effects of clay stabilizers on the compressive and tensile strength of the rocks. Results showed that clay stabilizers reduced clay swelling and decreased the strength of the rocks. Additionally, medical CT scans confirmed the presence and growth of a fracture network.
Article
Energy & Fuels
Kang Duan, Yingchun Li, Wendong Yang
Summary: The study investigates the impact of well distance, spacing between injection points, and arrangement of injection points on hydraulic fracturing efficiency. It was found that the distance between wells only enhances efficiency when the spacing reaches 40 m, and increasing the spacing between injection points effectively mitigates stress shadowing effect and promotes fracturing efficiency when the distance exceeds 60 m. Arrangement of injection points has a negligible role compared to the spacing among them.
GEOMECHANICS AND GEOPHYSICS FOR GEO-ENERGY AND GEO-RESOURCES
(2021)
Article
Engineering, Mechanical
Xiaoli Su, Diyuan Li, Quanqi Zhu, Jinyin Ma
Summary: This study investigated the effects of fatigue loads on hydraulic fracturing in granite under different stress states. The results showed that the amplitudes of cyclic load had a significant impact on fracture initiation pressure and fracture morphology. Higher amplitude disturbance in the intermediate principal stress direction resulted in lower breakdown pressure and wider fractures. Increasing disturbance frequency led to the generation of complex fatigue cracks, which could weaken the rock strength.
FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES
(2023)
Article
Energy & Fuels
Chengzheng Cai, Zhixiang Tao, Keda Ren, Shuang Liu, Yugui Yang, Yinrong Feng, Shanjie Su, Peng Hou
Summary: Liquid nitrogen (LN) fracturing has been proven to be an efficient technology for developing unconventional gas resources. Experimental results showed that increasing the initial rock temperature reduces the breakdown pressure of sandstone, while under cryogenic conditions, the fracture complexity is significantly improved despite a potential increase in breakdown pressure.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2021)
Article
Engineering, Chemical
Olalekan Alade, Lei Gang, Zeeshan Tariq, Mohamed Mahmoud, Dhafer Al Shehri, Abdullah Sultan, Ammar Al-Ramadhan, Esmail Mokheimer
Summary: Thermogravimetric analysis (TGA) was used to study the decomposition behavior of bitumen under high pressure non-isothermal conditions, with kinetic parameters optimized using simulated annealing (SA) algorithm. The results showed that weight loss and thermal conversion of bitumen decreased with increasing total pressure, and the thermal conversion rate varied in different temperature regions. Ultimately, the study demonstrated that the SA algorithm could enhance the performance of differential modelling in calculating kinetic parameters and predicting conversion rates.
CANADIAN JOURNAL OF CHEMICAL ENGINEERING
(2022)
Article
Energy & Fuels
Osama Mutrif Siddig, Saad Fahaid Al-Afnan, Salaheldin Mahmoud Elkatatny, Abdulazeez Abdulraheem
Summary: This article aims to create a continuous profile of Young's modulus using drilling rig sensor records. Three machine learning algorithms were used to correlate drilling data with Young's modulus, and satisfactory results were obtained. This approach shows promise for predicting geomechanical properties using drilling data and artificial intelligence techniques.
JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME
(2022)
Review
Biochemistry & Molecular Biology
Muhammad Naeem, Amjad Bajes Khalil, Zeeshan Tariq, Mohamed Mahmoud
Summary: During the fracture stimulation process of oil and gas wells, fracturing fluids are used to create fractures and transport proppants. The viscosity of the fracturing fluid can be increased through the use of guar polymer and cross-linkers, and decreased by breakers for efficient oil and gas recovery. Enzyme breakers have been developed to reduce the fluid viscosity, but thermal stability remains a challenge. Recent advancements in enzyme engineering techniques show promise in enhancing the thermostability of enzyme breakers in the upstream oil and gas industry.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Nanoscience & Nanotechnology
Faizan Ali, Muhammad Arqam Khan, Ghulam Haider, Adnan ul-Haque, Zeeshan Tariq, Ayesha Nadeem
Summary: This study reveals the potential of machine learning models, such as decision tree and extreme gradient boosting, in predicting the expected oil recovery from silica nano-fluid flooding in sandstone reservoirs. The importance of rock porosity, rock permeability, nano-particle concentration, and oil density on additional oil recovery is highlighted.
APPLIED NANOSCIENCE
(2022)
Review
Biotechnology & Applied Microbiology
Sulaiman A. Alarifi, Ayyaz Mustafa, Kamal Omarov, Abdul Rehman Baig, Zeeshan Tariq, Mohamed Mahmoud
Summary: Enzyme-induced calcium carbonate precipitation (EICP) techniques have various applications, especially in solving sand production issues in the oil and gas industry. The use of bio-cementation techniques for sand consolidation has gained interest due to their sustainability and environmental friendliness. This study provides a guideline for assessing sand consolidation performance and the applicability of EICP in mitigating sand production problems in oil and gas wells.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2022)
Article
Geosciences, Multidisciplinary
Ayyaz Mustafa, Zeeshan Tariq, Abdulazeez Abdulraheem, Mohamed Mahmoud, Shams Kalam, Rizwan Ahmed Khan
Summary: This study develops a predictive model for the rock brittleness index (BI) using a machine learning approach and well-log data. The proposed model outperforms traditional models in terms of accuracy and provides more accurate predictions of the brittleness index in shale reservoirs.
Article
Chemistry, Multidisciplinary
Zeeshan Tariq, Bicheng Yan, Shuyu Sun, Manojkumar Gudala, Murtada Saleh Aljawad, Mobeen Murtaza, Mohamed Mahmoud
Summary: In this study, machine learning models were efficiently utilized to predict the breakdown pressure of unconventional rocks. A comprehensive hydraulic fracturing experimental study was conducted on various rock specimens, and the rock mechanical properties and experimental conditions were correlated using machine learning techniques. The accuracy of all machine learning models was similar, with an accuracy of 95% in predicting the breakdown pressure. The proposed methodology can minimize experimental costs and be used as a quick assessment tool for evaluating the development prospect of unconventional tight rocks.
Article
Multidisciplinary Sciences
Ayyaz Mustafa, Zeeshan Tariq, Mohamed Mahmoud, Abdulazeez Abdulraheem
Summary: This study predicts NMR porosity using three different machine learning algorithms and finds that the artificial neural network (ANN) model performs the best with high correlation coefficient and low errors compared to the actual dataset. This research demonstrates the successful application of machine learning techniques in accurately predicting NMR porosity.
SCIENTIFIC REPORTS
(2023)
Article
Energy & Fuels
Amro Othman, Zeeshan Tariq, Murtada Saleh Aljawad, Bicheng Yan, Muhammad Shahzad Kamal
Summary: The researchers conducted rheology experiments to optimize fracture fluid viscosity in high salinity mediums. Through machine learning models, they found that the feedforward neural network outperformed other models in predicting viscosity with 95% accuracy.
Article
Energy & Fuels
Manojkumar Gudala, Suresh Kumar Govindarajan, Zeeshan Tariq, Bicheng Yan, Shuyu Sun
Summary: The Puga geothermal reservoir in India has shown potential for geothermal energy extraction, however, there have been limited studies on its thermo-hydrogeomechanical behavior. This study enhances the THM model and proposes an integrated assessment approach to improve heat extraction possibilities. The evaluation results demonstrate the effectiveness of the proposed techniques. Overall, the article highlights the importance of understanding the behavior of geothermal reservoirs and provides valuable insights for future geothermal energy exploitation.
GEOENERGY SCIENCE AND ENGINEERING
(2023)
Article
Energy & Fuels
Bicheng Yan, Chen Li, Zeeshan Tariq, Kai Zhang
Summary: In this study, a deep learning approach called Inversion Neural Network (INN) is proposed to infer reservoir model parameters using transient pressure data. The results demonstrate that the INN can accurately predict fluid flow in porous media by inverting pressure derivative data. The use of convolutional neural network and transfer learning further improves the accuracy in heterogeneous scenarios.
GEOENERGY SCIENCE AND ENGINEERING
(2023)
Article
Energy & Fuels
Zeeshan Tariq, Manojkumar Gudala, Bicheng Yan, Shuyu Sun, Mohamed Mahmoud
Summary: This study used six machine learning techniques to predict the NMR-based effective porosity in carbonate rocks, achieving accurate results. The study also provided an empirical model for quickly estimating NMR-based effective porosity, based on well logs.
GEOENERGY SCIENCE AND ENGINEERING
(2023)
Article
Multidisciplinary Sciences
Adel Mohamed Salem, Mohamed Attia, Ahmed Alsabaa, Ahmed Abdelaal, Zeeshan Tariq
Summary: An accurate value of compressibility factor is critical for petroleum engineering. This study applied machine learning techniques to predict the gas compressibility factor and extracted an empirical equation for conversion. The results showed that the ANN-based model outperformed other models and the proposed correlation had lower errors.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2022)
Article
Multidisciplinary Sciences
Ashraf Ahmed, Salaheldin Elkatatny, Hany Gamal, Abdulazeez Abdulraheem
Summary: This study developed several artificial intelligence models for real-time prediction of bulk density in complex lithology using drilling parameters as inputs. Validation on data from both a vertical well and another well demonstrated the reliability and high accuracy of the models in predicting bulk density.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2022)
Article
Multidisciplinary Sciences
Ammar Abdlmutalib, Osman Abdullatif, Abdulazeez Abdulraheem, Mohamed Yassin
Summary: This study evaluated the main factors controlling rock strength and elastic properties of three carbonate mudrocks units in Central Saudi Arabia's Jurassic succession. Weak to moderate correlations were observed between mechanical properties and porosity, as well as between particle size and unconfined compressive strength. The sedimentary layering and associated anisotropy significantly control these correlations.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2022)