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This study proposes a novel method to investigate the effects of friction reducers on the microstructure and permeability of gas shale, using the Longmaxi formation as a case study. By combining high-pressure mercury injection (HPMI) data, the pore size distributions (PSDs) and permeability of gas shale sample were derived from low-field nuclear magnetic resonance (NMR) T spectra under various immersion time conditions. The results demonstrate that this method effectively illustrates the impact of friction reducer on gas shale microstructure across different immersion durations. The proportions of both micro- and macro-pores increase initially, then decrease, and eventually stabilize, peaking at 1 day. Meso-pores follow a different trend, with the maximum occurring at 5 days. Permeability trends correspond with micro- and macro- pore changes, and the permeability ratio remains above 1.0, confirming enhanced permeability. These findings provide insight into optimizing friction reducer formulations and improving shale gas extraction efficiency.
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http://dx.doi.org/10.1038/s41598-025-10167-y | DOI Listing |
ACS Omega
September 2025
National Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, Sichuan 610500, China.
Conventional acidizing struggles to remove complex, organic-rich scales in oil wells, and while strong organic solvents can help, their high cost and safety risks limit field use. To overcome these shortcomings, we developed a low-cost, safe permeability-enhanced-dispersion (PD) technique that first loosens and disperses the scale and then applies acid for thorough cleanup. The PD fluid (DL) contains a mutually soluble fatty alcohol amide phosphate dispersant (DL-F), ethanol, a surfactant blend, and a self-generating acid.
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August 2025
State Key Laboratory of Shale Oil and Gas Enrichment Mechanisms and Efficient Development, SINOPEC, Beijing 102206, China.
The quantification of movable shale oil is crucial for the effective exploration and development of shale oil resources. Nuclear magnetic resonance (NMR), a nondestructive and noninvasive technique, has become an indispensable tool for evaluating movable oil saturation. However, the small core sizes, high-frequency instrumentation, costly measurements, and significant losses of light hydrocarbons pose substantial challenges in accurately assessing movable oil.
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September 2025
Guangdong Aerospace Research Academy, Guangzhou, China.
The imbibition of water into the pores of tight oil/gas reservoir can displace the oil/gas out. Thus it is an important method to improve the recovery efficiency of tight shale gas and oil. This paper investigated the influence of four main dimensionless parameters on the spontaneous imbibition based on a pores distribution of a real shale sample.
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August 2025
Department of Mechanical Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
The unconfined compressive strength of organic-rich clay shale is a fundamental parameter in geotechnical and energy applications, influencing drilling efficiency, wellbore stability, and excavation design. This study presents machine learning-based predictive models for unconfined compressive strength estimation, trained on a comprehensive dataset of 1217 samples that integrate non-destructive indicators such as ultrasonic pulse velocity, shale fabric metrics, wettability potential and destructive field-derived parameters. A dual-model framework was implemented using Support Vector Machine, Decision Tree, K-Nearest Neighbor, and Extreme Gradient Boosting (XGBoost) algorithms.
View Article and Find Full Text PDFEnviron Manage
August 2025
Department of Geology and Geography, West Virginia University, Morgantown, WV, USA.
Managing produced water in unconventional oil and gas (UOG) industry is a growing environmental challenge as shale development expands globally. This study evaluates the operational and economic impacts of restricting produced water disposal in southwestern Pennsylvania, where concerns over injection wells and evaporation ponds are rising. We develop a regional mixed-integer programming model calibrated using data from 11,217 wells between 2015 and 2022.
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