Integrated Characterization of the Fracture Network in Fractured Shale Gas Reservoirs—Stochastic Fracture Modeling, Simulation and Assisted History Matching

2019 ◽  
Author(s):  
Yonghui Wu ◽  
Linsong Cheng ◽  
John E. Killough ◽  
Shijun Huang ◽  
Sidong Fang ◽  
...  
Keyword(s):  
Shale Gas ◽  
History Matching ◽  
Fracture Network ◽  
Gas Reservoirs ◽  
Modeling Simulation ◽  
Shale Gas Reservoirs ◽  
Fracture Modeling ◽  
Assisted History Matching

Integrated Characterization of Hydraulically Fractured Shale Gas Reservoirs Production History Matching

2014 ◽  
Author(s):  
Siavash Nejadi ◽  
Juliana Yuk Wing Leung ◽  
Japan J Trivedi ◽  
Claudio Juan Jose Virues
Keyword(s):  
Shale Gas ◽  
History Matching ◽  
Gas Reservoirs ◽  
Shale Gas Reservoirs ◽  
Production History

An Integrated Assisted History Matching and Embedded Discrete Fracture Model Workflow for Well Spacing Optimization in Shale Gas Reservoirs

2021 ◽  
pp. 1-29
Author(s):  
Qiwei Li ◽  
Rui Yong ◽  
Jianfa Wu ◽  
Cheng Chang ◽  
Chuxi Liu ◽  
...  
Keyword(s):  
Shale Gas ◽  
History Matching ◽  
Essential Element ◽  
Fracture Model ◽  
Gas Reservoirs ◽  
Discrete Fracture Model ◽  
Shale Gas Reservoirs ◽  
Well Spacing ◽  
Discrete Fracture ◽  
Assisted History Matching

Abstract Optimum well spacing is an essential element for the economic development of shale gas reservoirs. We present an integrated assisted history matching (AHM) and embedded discrete fracture model (EDFM) workflow for well spacing optimization by considering multiple uncertainty realizations and economic analysis. This workflow is applied in shale gas reservoirs of the Sichuan Basin in China. Firstly, we applied the AHM to calibrate ten matrix and fracture uncertain parameters using a real shale-gas well, including matrix permeability, matrix porosity, three relative permeability parameters, fracture height, fracture half-length, fracture width, fracture conductivity, and fracture water saturation. There are 71 history matching solutions obtained to quantify their posterior distributions. Integrating these uncertainty realizations with five well spacing scenarios, which are 517 ft, 620 ft, 775 ft, 1030 ft, and 1550 ft, we generated 355 cases to perform production simulations using the EDFM method coupled with a reservoir simulator. Then, P10, P50, and P90 values of gas estimated ultimate recovery (EUR) for different well spacing scenarios were determined. Additionally, the degradation of EUR with and without well interference was analyzed. Next, we calculated the NPVs of all simulation cases and trained the K-Nearest Neighbors (KNN) proxy, which describes the relationship between the NPV and all uncertain matrix and fracture parameters and varying well spacing. After that, the KNN proxy was used to maximize the NPV under the current operation cost and natural gas price. Finally, the maximum NPV of 3 million USD with well spacing of 766 ft was determined.

History Matching of Stimulated Reservoir Volume of Shale-Gas Reservoirs Using an Iterative Ensemble Smoother

SPE Journal ◽  
2017 ◽  
Vol 23 (02) ◽  
pp. 346-366 ◽  
Author(s):  
Haibin Chang ◽  
Dongxiao Zhang
Keyword(s):  
Hydraulic Fracturing ◽  
Shale Gas ◽  
History Matching ◽  
Fracture Network ◽  
Hydraulic Fractures ◽  
Gas Reservoirs ◽  
Stimulated Reservoir Volume ◽  
Reservoir Volume ◽  
Shale Gas Reservoirs ◽  
Iterative Ensemble Smoother

Summary Economic production from shale-gas reservoirs typically relies on the drilling of horizontal wells and hydraulic fracturing in multiple stages. In addition to the creation of hydraulic fractures, hydraulic-fracturing treatment can also reopen existing natural fractures, which can create a complex-fracture network. The area that is covered by the fracture network is usually termed the stimulated reservoir volume (SRV), and the spatial extent and properties of the SRV are crucial for shale-gas-production behavior. In this work, we propose a method for history matching of the SRV of shale-gas reservoirs using production data. For each hydraulic-fracturing stage, the fracture network is parameterized with one major fracture of the hydraulic fractures and the SRV that represents minor hydraulic fractures and reopened natural fractures. The major fracture is modeled explicitly, whereas the SRV is modeled by the dual-permeability/dual-porosity (DP/DP) model. Moreover, the spatial extent of the SRV is parameterized by the level-set-function values on a predefined representing-node system. After parameterization, an iterative ensemble smoother is used to perform history matching. Both single-stage-fracturing cases and multistage-fracturing cases are set up to test the performance of the proposed method. Numerical results demonstrate that by use of the proposed method, the SRV can be well-recognized by assimilating production data.

Multidisciplinary Approach for Detailed Characterization of Shale Gas Reservoirs: A Netherlands Showcase

2013 ◽  
Author(s):  
Yvonne Anja Schavemaker ◽  
Mart Zijp ◽  
Jan ter Heege ◽  
Susanne Nelskamp ◽  
Johan Ten Veen
Keyword(s):  
Shale Gas ◽  
Multidisciplinary Approach ◽  
Gas Reservoirs ◽  
Detailed Characterization ◽  
Shale Gas Reservoirs

scholarly journals A New Approach for Automatic Optimization of Complex Fracture Network in Shale Reservoirs

Lithosphere ◽  
2021 ◽  
Vol 2021 (Special 1) ◽  
Author(s):  
Haibo Wang ◽  
Tong Zhou ◽  
Fengxia Li
Keyword(s):  
Shale Gas ◽  
Flow Model ◽  
Optimization Method ◽  
Fracture Network ◽  
Gas Reservoirs ◽  
Fracture Length ◽  
Complex Fracture ◽  
Shale Gas Reservoirs ◽  
Automatic Optimization ◽  
Complex Fracture Network

Abstract Shale gas reservoirs have gradually become the main source for oil and gas production. The automatic optimization technology of complex fracture network in fractured horizontal wells is the key technology to realize the efficient development of shale gas reservoirs. In this paper, based on the flow model of shale gas reservoirs, the porosity/permeability of the matrix system and natural fracture system is characterized. The fracture network morphology is finely characterized by the fracture network expansion calculation method, and the flow model was proposed and solved. On this basis, the influence of matrix permeability, matrix porosity, fracture permeability, fracture porosity, and fracture length on the production of shale gas reservoirs is studied. The optimal design of fracture length and fracture location was carried, and the automatic optimization method of complex fracture network parameters based on simultaneous perturbation stochastic approximation (SPSA) was proposed. The method was applied in a shale gas reservoir, and the results showed that the proposed automatic optimization method of the complex fracture network in shale gas reservoirs can automatically optimize the parameters such as fracture location and fracture length and obtain the optimal fracture network distribution matching with geological conditions.

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