|
[1]
|
邹才能, 董大忠, 王社教, 等. 中国页岩气形成机理、地质特征及资源潜力[J]. 石油勘探与开发, 2010, 37(6): 641-653.
|
|
[2]
|
Kang, Y., You, L., Xu, X. and Liao, Z. (2012) Prevention of Formation Damage Induced by Mud Lost in Deep Fractured Tight Gas Reservoir in Western Sichuan Basin. Journal of Canadian Petroleum Technology, 51, 46-51. [Google Scholar] [CrossRef]
|
|
[3]
|
孙金声, 白英睿, 程荣超, 等. 裂缝性恶性井漏地层堵漏技术研究进展与展望[J]. 石油勘探与开发, 2021, 48(3): 630-638.
|
|
[4]
|
王中华. 复杂漏失地层堵漏技术现状及发展方向[J]. 中外能源, 2014(1): 39.
|
|
[5]
|
张希文, 李爽, 张洁, 等. 钻井液堵漏材料及防漏堵漏技术研究进展[J]. 钻井液与完井液, 2009, 26(6): 74-76+79+97.
|
|
[6]
|
彭浩. 裂缝性地层井漏分析与堵漏决策优化研究[D]: [硕士学位论文]. 成都: 西南石油大学, 2016.
|
|
[7]
|
吕开河. 钻井工程中井漏预防与堵漏技术研究与应用[D]: [博士学位论文]. 大庆: 东北石油大学, 2007.
|
|
[8]
|
李大奇, 康毅力, 刘修善, 等. 基于漏失机理的碳酸盐岩地层漏失压力模型[J]. 石油学报, 2011, 32(5): 900-904.
|
|
[9]
|
曾义金, 李大奇, 杨春和. 裂缝性地层防漏堵漏力学机制研究[J]. 岩石力学与工程学报, 2016, 35(10): 2054-2061.
|
|
[10]
|
刘加杰, 康毅力, 王业众. 扩展钻井液安全密度窗口理论与技术进展[J]. 钻井液与完井液, 2007(4): 69-73+98-99.
|
|
[11]
|
皇凡生. 天然裂缝网络系统钻井完井液漏失数值模拟[D]: [硕士学位论文]. 成都: 西南石油大学, 2014.
|
|
[12]
|
李松. 海相碳酸盐岩层系钻井液漏失诊断基础研究[D]: [博士学位论文]. 成都: 西南石油大学, 2014.
|
|
[13]
|
王斌. 裂缝性漏层钻井液漏失与堵漏计算机模拟研究[D]: [硕士学位论文]. 成都: 西南石油大学, 2019.
|
|
[14]
|
Majidi, R., Miska, S.Z., Yu, M. and Thompson, L.G. (2008) Fracture Ballooning in Naturally Fractured Formations: Mechanism and Controlling Factors. SPE Annual Technical Conference and Exhibition, Denver, September 2008, SPE-115526-MS. [Google Scholar] [CrossRef]
|
|
[15]
|
Wang, H., Towler, B. and Soliman, M. (2007) Fractured Wellbore Stress Analysis: Sealing Cracks to Strengthen a Wellbore. Proceedings of SPE/IADC Drilling Conference, Amsterdam, February 2007, SPE-104947-MS. [Google Scholar] [CrossRef]
|
|
[16]
|
Warren, J.E. and Root, P.J. (1963) The Behavior of Naturally Fractured Reservoirs. Society of Petroleum Engineers Journal, 3, 245-255. [Google Scholar] [CrossRef]
|
|
[17]
|
Barenblatt, G.I., Zheltov, I.P. and Kochina, I.N. (1960) Basic Concepts in the Theory of Seepage of Homogeneous Liquids in Fissured Rocks [Strata]. Journal of Applied Mathematics and Mechanics, 24, 1286-1303. [Google Scholar] [CrossRef]
|
|
[18]
|
Sanfillippo, F., Brignoli, M., Santarelli, F.J. and Bezzola, C. (1997) Characterization of Conductive Fractures While Drilling. SPE European Formation Damage Conference, The Hague, June 1997, SPE-38177-MS. [Google Scholar] [CrossRef]
|
|
[19]
|
Dershowitz, W.S. and Einstein, H.H. (1988) Characterizing Rock Joint Geometry with Joint System Models. Rock Mechanics and Rock Engineering, 21, 21-51. [Google Scholar] [CrossRef]
|
|
[20]
|
Tempone, P. and Lavrov, A. (2008) DEM Modeling of Mud Losses into Single Fractures and Fracture Network. 12th International Conference of International Association for Computer Methods and Advances in Geomechanics, Goa, 1-6 October 2008, 10-13.
|
|
[21]
|
Karimi-Fard, M., Durlofsky, L.J. and Aziz, K. (2004) An Efficient Discrete-Fracture Model Applicable for General-Purpose Reservoir Simulators. SPE Journal, 9, 227-236. [Google Scholar] [CrossRef]
|
|
[22]
|
Lavrov, A. and Tronvoll, J. (2004) Modeling Mud Loss in Fractured Formations. Abu Dhabi International Conference and Exhibition, Abu Dhabi, October 2004, SPE-88700-MS. [Google Scholar] [CrossRef]
|
|
[23]
|
Fang, J., Zhou, F. and Tang, Z. (2017) Discrete Fracture Network Modelling in a Naturally Fractured Carbonate Reservoir in the Jingbei Oilfield, China. Energies, 10, Article No. 183. [Google Scholar] [CrossRef]
|
|
[24]
|
Feng, Y. and Gray, K.E. (2017) Modeling Lost Circulation through Drilling-Induced Fractures. SPE Journal, 23, 205-223. [Google Scholar] [CrossRef]
|
|
[25]
|
Kim, Y.D. and Durlofsky, L.J. (2023) Convolutional-Recurrent Neural Network Proxy for Robust Optimization and Closed-Loop Reservoir Management. Computational Geosciences, 27, 179-202. [Google Scholar] [CrossRef]
|
|
[26]
|
Guo, Y. (2024) Multi-Scale Chemo-Mechanical Coupling Effects for Fluid-Infiltrating Porous Media: Theory, Implementation, and Validation.
|
|
[27]
|
Yaghoubi, A. (2019) Hydraulic Fracturing Modeling Using a Discrete Fracture Network in the Barnett Shale. International Journal of Rock Mechanics and Mining Sciences, 119, 98-108. [Google Scholar] [CrossRef]
|
|
[28]
|
Sahimi, M. and Tahmasebi, P. (2022) The Potential of Quantum Computing for Geoscience. Transport in Porous Media, 145, 367-387. [Google Scholar] [CrossRef]
|
|
[29]
|
Zhang, T., Zhu, P. and Lu, F. (2023) Stochastic Reconstruction of Porous Media Based on Attention Mechanisms and Multi-Stage Generative Adversarial Network. Computational Geosciences, 27, 515-536. [Google Scholar] [CrossRef]
|
|
[30]
|
Lee, J. and Chang, J.S. (2024) Physics-Informed Neural Network Model for Predictive Risk Assessment and Safety Analysis. Transportation Research Record: Journal of the Transportation Research Board. [Google Scholar] [CrossRef]
|