Simulation and history matching of a shale gas reservoir using different models in eagle ford basin

2015 ◽  
pp. 67-73
Author(s):  
D.-F. Zhao ◽  
◽  
Y.-H. Guo ◽  
C.-G. Xiang ◽  
J.-Ch. Zang
Keyword(s):  
Shale Gas ◽  
History Matching ◽  
Gas Reservoir ◽  
Eagle Ford ◽  
Shale Gas Reservoir

scholarly journals Multi-Objective History Matching with a Proxy Model for the Characterization of Production Performances at the Shale Gas Reservoir

Energies ◽  
2017 ◽  
Vol 10 (4) ◽  
pp. 579 ◽  
Author(s):  
Jaejun Kim ◽  
Joe Kang ◽  
Changhyup Park ◽  
Yongjun Park ◽  
Jihye Park ◽  
...  
Keyword(s):  
Shale Gas ◽  
History Matching ◽  
Gas Reservoir ◽  
Multi Objective ◽  
Shale Gas Reservoir ◽  
Proxy Model

scholarly journals Development of Production-Forecasting Model Based on the Characteristics of Production Decline Analysis Using the Reservoir and Hydraulic Fracture Parameters in Montney Shale Gas Reservoir, Canada

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Hyeonsu Shin ◽  
Viet Nguyen-Le ◽  
Min Kim ◽  
Hyundon Shin ◽  
Edward Little
Keyword(s):  
Shale Gas ◽  
Hydraulic Fracture ◽  
History Matching ◽  
Forecasting Model ◽  
Gas Reservoir ◽  
Shale Gas Reservoir ◽  
Production Forecasting ◽  
Fracture Parameters ◽  
Decline Rate ◽  
Cumulative Production

This study developed a production-forecasting model to replace the numerical simulation and the decline curve analysis using reservoir and hydraulic fracture data in Montney shale gas reservoir, Canada. A shale-gas production curve can be generated if some of the decline parameters such as a peak rate, a decline rate, and a decline exponent are properly estimated based on reservoir and hydraulic fracturing parameters. The production-forecasting model was developed to estimate five decline parameters of a modified hyperbolic decline by using significant reservoir and hydraulic fracture parameters which are derived through the simulation experiments designed by design of experiments and statistical analysis: (1) initial peak rate ( P hyp ), (2) hyperbolic decline rate ( D hyp ), (3) hyperbolic decline exponent ( b hyp ), (4) transition time ( T transition ), and (5) exponential decline rate ( D exp ). Total eight reservoir and hydraulic fracture parameters were selected as significant parameters on five decline parameters from the results of multivariate analysis of variance among 11 reservoir and hydraulic fracture parameters. The models based on the significant parameters had high predicted R 2 values on the cumulative production. The validation results on the 1-, 5-, 10-, and 30-year cumulative production data obtained by the simulation showed a good agreement: R 2 > 0.89 . The developed production-forecasting model can be also applied for the history matching. The mean absolute percentage error on history matching was 5.28% and 6.23% for the forecasting model and numerical simulator, respectively. Therefore, the results from this study can be applied to substitute numerical simulations for the shale reservoirs which have similar properties with the Montney shale gas reservoir.

Simulation and history matching of a shale gas reservoir using different models in Eagle Ford Basin

2012 ◽  
Vol 52 (2) ◽  
pp. 648
Author(s):  
Bingxiang Xu ◽  
Manouchehr Haghighi ◽  
D Cooke
Keyword(s):  
History Matching ◽  
Dual Porosity ◽  
Production Data ◽  
Gas Reservoir ◽  
Eagle Ford ◽  
Shale Gas Reservoir ◽  
Production Forecasting ◽  
Dual Porosity Model ◽  
Early Production ◽  
Porosity Model

Eagle Ford Shale in South Texas is one of the recent shale play in the US, which began developing in late 2008. To evaluate the reservoir performance and make the production forecasting for this reservoir, one multi-stage fractured horizontal well was modelled and history matching was done using the available 250 days of production data. Two different flow models of dual-porosity and multi-porosity have been examined. In the multi-porosity model, both approaches of instant and time-dependent sorption have been investigated. Also, two approaches of negative skin and transverse fractures were used to model the effect of hydraulic fracturing. For history matching of early production data, all the models were successfully matched; however, all models predict differently for production forecasting. Comparing both production forecasts for 10 years, the multi-porosity model forecasts 14% more than dual-porosity model. This is because in the dual-porosity model, only free porosity is considered and no adsorbed gas in micro-pores is assumed; in multi-porosity model, both macro and micro porosities are active in shale gas reservoir. It is concluded that the early production data is not reliable to validate the simulation and make the production forecasting. This is because in early production data, all gas are produced from the fracture system and the matrix contribution is not significant or it has not been started yet. Furthermore, the effect of matrix sub-division on the simulation was studied: the free gas in matrix can contribute to production more quickly when matrix sub-cells increase.

scholarly journals A Novel Optimization Workflow Coupling Statistics-Based Methods to Determine Optimal Well Spacing and Economics in Shale Gas Reservoir with Complex Natural Fractures

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3965
Author(s):  
Cheng Chang ◽  
Chuxi Liu ◽  
Yongming Li ◽  
Xiaoping Li ◽  
Wei Yu ◽  
...  
Keyword(s):  
Shale Gas ◽  
History Matching ◽  
Net Present Value ◽  
Hydraulic Fractures ◽  
Natural Fractures ◽  
Gas Reservoirs ◽  
Gas Reservoir ◽  
Shale Gas Reservoir ◽  
Shale Gas Reservoirs ◽  
Well Spacing

In order to account for big uncertainties such as well interferences, hydraulic and natural fractures’ properties and matrix properties in shale gas reservoirs, it is paramount to develop a robust and efficient approach for well spacing optimization. In this study, a novel well spacing optimization workflow is proposed and applied to a real shale gas reservoir with two-phase flow, incorporating the systematic analysis of uncertainty reservoir and fracture parameters. One hundred combinations of these uncertainties, considering their interactions, were gathered from assisted history matching solutions, which were calibrated by the actual field production history from the well in the Sichuan Basin. These combinations were used as direct input to the well spacing optimization workflow, and five “wells per section” spacing scenarios were considered, with spacing ranging from 157 m (517 ft) to 472 m (1550 ft). An embedded discrete fracture model was used to efficiently model both hydraulic fractures and complex natural fractures non-intrusively, along with a commercial compositional reservoir simulator. Economic analysis after production simulation was then carried out, by collecting cumulative gas and water production after 20 years. The net present value (NPV) distributions of the different well spacing scenarios were calculated and presented as box-plots with a NPV ranging from 15 to 35 million dollars. It was found that the well spacing that maximizes the project NPV for this study is 236 m (775 ft), with the project NPV ranging from 15 to 35 million dollars and a 50th percentile (P50) value of 25.9 million dollars. In addition, spacings of 189 m (620 ft) and 315 m (1033 ft) can also produce substantial project profits, but are relatively less satisfactory than the 236 m (775 ft) case when comparing the P25, P50 and P75 values. The results obtained from this study provide key insights into the field pilot design of well spacing in shale gas reservoirs with complex natural fractures.

Production Data Analysis in Eagle Ford Shale Gas Reservoir

2012 ◽  
Author(s):  
Bingxiang Xu ◽  
Manouchehr Haghighi ◽  
Dennis A. Cooke ◽  
XiangFang Li
Keyword(s):  
Data Analysis ◽  
Shale Gas ◽  
Production Data ◽  
Eagle Ford Shale ◽  
Gas Reservoir ◽  
Eagle Ford ◽  
Shale Gas Reservoir
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