Development of one dimensional geomechanical model for a tight gas reservoir

Abstract 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 re...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Abhiram Kumar Verma, Debasis Deb, Akshay Chandan Dey, Subrata Roy, Ajay Kumar Singh, V. L. N. Avadhani, Rajiv Ranjan Tiwari
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
R
Q
Acceso en línea:https://doaj.org/article/891f22e420b8454292b4b2ad25b9b35c
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:Abstract 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.