Advanced three-dimensional reservoir geomechanical modeling for enhanced characterization and stress profile predication of oil and gas reservoirs
Reservoir characterization, assessing rock mechanical properties, and stress state are essential factors for exploration and development of a hydrocarbon or geothermal reservoir. Computing three-dimensional (3D) geospatial distribution of reservoir geomechanical properties on a reservoir scale becomes challenging, particularly when data are constrained to well locations and complex stress variation within the local anticline structure. To confront such challenges, advanced geostatistical techniques are essential to apply to capture the intrinsic spatial variation of reservoir geomechanical properties precisely. Therefore, this research examines the spatial variability of major mechanical rock parameters, pore pressure, principal stresses, and petrophysical properties of the Baikouquan Formation within the D1 well block, Mahu Sag, China. The dataset consists of seventeen wells and enables the construction of the reservoir's one-dimensional (1D) model, geomechanical parameters, and unified laboratory measurements for calibration of each well. Subsequently, a 3D model is developed via geostatistical simulation techniques, integrating well logs, seismic data, and core data reservoir geomechanical analysis. The modeling results show that the minimum and maximum horizontal stresses are 74–84 MPa and 95–106 MPa, respectively. However, the orientation of maximum horizontal stress was identified as northeast-southwest (NE- SW) and east-west (E-W). This investigation highlights the productiveness of 3D modeling by providing a detailed portrayal and knowledge of pre-production stress state and geomechanical parameters assessment to execute a variety of subsurface operations safely. In addition, it provides a platform for evaluating forthcoming strategies in the reservoir, such as determining the optimal spot and designing new well trajectory for field development and arbitrary scenarios.
Authors
- Sayed Muhammad Iqbal (ORCID: https://orcid.org/0000-0001-9008-3775)
- Leiming Cheng
- Qian Wang (ORCID: https://orcid.org/0000-0001-6266-8485)
- Shuang Tian
- Hui Zhou (ORCID: https://orcid.org/0009-0007-5332-1982)
- Haoran Sun
- Dawei Hu
Institutions
- Institute of Rock and Soil Mechanics (CN)
- University of Chinese Academy of Sciences (CN)
- China National Petroleum Corporation (China) (CN)
Publication Details
- Journal
- Physics of Fluids
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1063/5.0229673
- Citations
- 7
- Primary Topic
- Seismic Imaging and Inversion Techniques
- Type
- article
- Field-Weighted Citation Impact
- 3.74
Funders
- National Natural Science Foundation of China-Xinjiang Joint Fund
- National Key Research and Development Program of China