Department of Mining Engineering, IIT Kharagpur, Kharagpur, West Bengal, India.
Centre for Excellence in Well Logging Technology (ONGC), Baroda, Gujrat, India.
Sci Rep. 2021 Nov 2;11(1):21433. doi: 10.1038/s41598-021-00860-z.
Estimating rock-mechanical, petrophysical properties and pre-production stress state is essential for effective reservoir planning, development, and optimal exploitation. This paper attempts to construct a comprehensive one-dimensional mechanical earth model (1D MEM) of the Mandapeta gas reservoir of Krishna Godavari (KG) basin, India. The methodology comprises a detailed stepwise process from processing and analysis of raw log data, calibration of log-derived dynamic properties with static ones using regression models developed from tested core samples, and final rock mechanical property estimation. Pore pressure profiles have been estimated and calibrated with the Repeat formation tester (RFT) data for every thirty-five wells. Overburden and horizontal stresses have also been evaluated and calibrated using data from the Leak-off Tests (LOT) or Extended Leak-off Tests (XLOT). A menu-driven program is developed using PYTHON code for visualization and on-time revision of 1D MEM. The resulting comprehensive 1D MEM predicts and establishes the rock-mechanical properties, pore pressure, and in-situ stress values of the basin. Besides its use in planning future wells, development of the field, and yielding insight into the various well challenges, it can also be used to develop a 3D MEM of the reservoir.
估算岩石力学、岩石物理性质和投产前的地应力状态对于有效的油藏规划、开发和优化开采至关重要。本文试图构建印度克里希纳戈达瓦里（KG）盆地曼达佩塔气藏的综合一维力学地球模型（1D MEM）。该方法包括从原始测井数据的处理和分析，到使用从测试岩心样本中开发的回归模型来校准测井衍生动态性质与静态性质，再到最终的岩石力学性质估算，这一系列详细的步骤。对每 35 口井都使用重复地层测试（RFT）数据来估算和校准孔隙压力剖面。还使用漏失试验（LOT）或扩展漏失试验（XLOT）的数据来评估和校准上覆压力和水平地应力。使用 PYTHON 代码开发了一个菜单驱动程序，用于可视化和及时修订 1D MEM。综合的 1D MEM 预测和建立了盆地的岩石力学性质、孔隙压力和原地应力值。除了用于规划未来的油井、开发油田以及深入了解各种油井挑战外，它还可以用于开发储层的 3D MEM。
