Petroleum Exploration and Development >
A smart productivity evaluation method for shale gas wells based on 3D fractal fracture network model
Received date: 2020-11-23
Revised date: 2021-05-07
Online published: 2021-08-25
Supported by
National Science and Technology Major Project(2017ZX05063-005);Science and Technology Development Project of PetroChina Research Institute of Petroleum Exploration and Development(YGJ2019-12-04)
The generation method of three-dimensional fractal discrete fracture network (FDFN) based on multiplicative cascade process was developed. The complex multi-scale fracture system in shale after fracturing was characterized by coupling the artificial fracture model and the natural fracture model. Based on an assisted history matching (AHM) using multiple-proxy-based Markov chain Monte Carlo algorithm (MCMC), an embedded discrete fracture modeling (EDFM) incorporated with reservoir simulator was used to predict productivity of shale gas well. When using the natural fracture generation method, the distribution of natural fracture network can be controlled by fractal parameters, and the natural fracture network generated coupling with artificial fractures can characterize the complex system of different- scale fractures in shale after fracturing. The EDFM, with fewer grids and less computation time consumption, can characterize the attributes of natural fractures and artificial fractures flexibly, and simulate the details of mass transfer between matrix cells and fractures while reducing computation significantly. The combination of AMH and EDFM can lower the uncertainty of reservoir and fracture parameters, and realize effective inversion of key reservoir and fracture parameters and the productivity forecast of shale gas wells. Application demonstrates the results from the proposed productivity prediction model integrating FDFN, EDFM and AHM have high credibility.
Yunsheng WEI , Junlei WANG , Wei YU , Yadong QI , Jijun MIAO , He YUAN , Chuxi LIU . A smart productivity evaluation method for shale gas wells based on 3D fractal fracture network model[J]. Petroleum Exploration and Development, 2021 , 48(4) : 911 -922 . DOI: 10.1016/S1876-3804(21)60076-9
| [1] | WANG Junlei, JIA Ailin, WEI Yunsheng, et al. Optimization workflow for stimulation-well spacing design in multiwall pad. Petroleum Exploration and Development, 2019, 46(5):915-921. |
| [2] | KUCHUK F, BIRYUKOV D. Pressure-transient behavior of continuously and discretely fractured reservoirs. SPE Reservoir Evaluation & Engineering, 2014, 17(1):82-97. |
| [3] | LIN Chengyan, LI Hui, MA Cunfei, et al. Modeling method of natural fractures in tight sandstone reservoirs. Journal of China University of Petroleum (Natural Science Edition), 2019, 43(5):21-33. |
| [4] | LANG Xiaoling, GUO Zhaojie. Fractured reservoir modeling method based on discrete fracture network model. Acta Scientiarum Naturalium Universitatis Pekinensisi (Natural Science Edition), 2013, 49(6):964-972. |
| [5] | AJISAFE F, THACHAPARAMBIL M, LEE D, et al. Calibrated complex fracture modeling using constructed discrete fracture network from seismic data in the Avalon Shale, New Mexico. SPE 179130-MS, 2016. |
| [6] | DREUZY J, DAVY P, ERHEL J, et al. Anomalous diffusion exponents in continuous two-dimensional multifractal media. Physical Review E Statistical Nonlinear & Soft Matter Physics, 2004, 70(1):016306. |
| [7] | LI Wei, ZHAO Huan, LI Siqi, et al. 2D characterization of geometric features and connectivity of fracture networks in shale formations. Petroleum Drilling Techniques, 2017, 45(6):70-76. |
| [8] | LIU R C, YU L Y, JIANG Y J, et al. Recent developments on relationships between the equivalent permeability and fractal dimension of two-dimensional rock fracture networks. Journal of Natural Gas Science and Engineering, 2017, 45:771-785. |
| [9] | KIM T H, SCHECHETER D S. Estimation of fracture porosity of naturally fractured reservoirs with no matrix porosity using fractal discrete fracture networks. SPE Reservoir Evaluation & Engineering, 2009, 12(2):232-242. |
| [10] | WU Minglu, DING Mingcai. A numerical well testing interpretation model for multiple fractured horizontal well in fractured shale gas reservoir based on fractal discrete fracture network. Journal of China University of Petroleum (Natural Science Edition), 2020, 44(3):98-104. |
| [11] | SUN J L, SCHECHTER D. Pressure-transient characteristics of fractured horizontal wells in unconventional shale reservoirs with construction of data-constrained discrete-fracture network. SPE Production & Operations, 2018, 33(1):21-31. |
| [12] | CIPOLLA C L, LOLON E P, ERDLE J C, et al. Reservoir modeling in shale-gas reservoirs. SPE 125530, 2009. |
| [13] | MIRZAEI M, CIPOLLA C L. A workflow for modeling and simulation of hydraulic fractures in unconventional gas reservoirs. SPE 153022, 2012. |
| [14] | KUCHUK F, BIRYUKOV D. Pressure-transient behavior of continuously and discretely fractured reservoirs. SPE Reservoir Evaluation & Engineering, 2014, 1:82-97. |
| [15] | KARIMI-FARD M, DURLOFSKY L J. A general gridding, discretization, and coarsening methodology for modeling flow in porous formations with discrete geological features. Advances in Water Resources, 2016, 96:354-372. |
| [16] | SU Hao, LEI Zhengdong, LI Junchao, et al. An effective numerical simulation model of multi-scale fractures in reservoir. Acta Petrolei Sinica, 2019, 40(5):587-594. |
| [17] | LI L, LEE S H. Efficient field-scale simulation of black oil in a naturally fractured reservoir through discrete fracture networks and homogenized media. SPE Reservoir Evaluation & Engineering, 2008, 11(4):750-758. |
| [18] | YU W, XU Y F, WEIJERMARS R, et al. A numerical model for simulating pressure response of well interference and well performance in tight oil reservoirs with complex- fracture geometries using the fast embedded-discrete- fracture-model method. SPE Reservoir Evaluation & Engineering, 2017, 21(2):489-502. |
| [19] | ZHU Dawei, HU Yongle, CUI Mingyue, et al. Productivity simulation of hydraulically fractured wells based on hybrid local grid refinement and embedded discrete fracture model. Petroleum Exploration and Development, 2020, 47(2):341-348. |
| [20] | YAN Xia, HUANG Zhaoqin, YAO Jun, et al. The embedded discrete fracture model based on mimetic finite difference method. Scientia Sinica Technologica, 2014, 44(12):1333-1342. |
| [21] | XUE Liang, WU Yujuan, LIU Qianjun, et al. Advances in numerical simulation and automatic history matching of fractured reservoirs. Petroleum Science Bulletin, 2019, 4(4):335-346. |
| [22] | DARCEL C, BOUR O, DAVY P, et al. Connectivity properties of two-dimensional fracture networks with stochastic fractal correlation. Water Resources Research, 2003, 39(10):1272. |
| [23] | SCHERTZER D, LOVEJOY S. Physical modeling and analysis of rain and clouds by anisotropic scaling multiplicative processes. Journal of Geophysical Research, 1987, 92(D8):96-93. |
| [24] | XU Y F, YU W, SEPEHRNOORI K. Modeling dynamic behaviors of complex fractures in conventional reservoir simulators. SPE Reservoir Evaluation & Engineering, 2019, 22(3):1110-1130. |
| [25] | TRIPOPPOOM S, YU W, HUANG H Y, et al. A practical and efficient iterative history matching workflow for shale gas well coupling multiple objective functions, multiple proxy-based MCMC and EDFM. Journal of Petroleum Science and Engineering, 2019, 176:594-611. |
| [26] | WEI Y, WANG J, JIA A, et al. Optimization of managed drawdown for a well with stress-sensitive conductivity fractures: Workflow and case study. Journal of Energy Resources Technology, 2021, 143(8):915-921. |
/
| 〈 |
|
〉 |