Estimation of Time of Peak Gas Production in Coalbed Methane Wells using Production Data Analysis

In shale gas reservoirs, the production data analysis method is widely used to invert reservoir and fracture parameter, and productivity prediction. Compared with numerical models and semianalytical models, which have high computational cost, the analytical model is mostly used in the production data analysis method to characterize the complex fracture network formed after fracturing. However, most of the current calculation models ignore the uneven support of fractures, and most of them use a single supported fracture model to describe the flow characteristics, which magnifies the role of supported fracture to a certain extent. Therefore, in this study, firstly, the fractures are divided into supported fractures and unsupported fractures. According to the near-well supported fractures and far-well unsupported fractures, the SRV zone is divided into outer SRV and inner SRV. The four areas are characterized by different seepage models, and the analytical solutions of the models are obtained by Laplace transform and inverse transform. Secondly, the material balance pseudotime is introduced to process the production data under the conditions of variable production and variable pressure. The double logarithmic curves of normalized production rate, rate integration, the derivative of the integration, and material balance pseudotime are established, and the parameters are interpreted by fitting the theoretical curve to the measured data. Then, the accuracy of the method is verified by comparison the parameter interpretation results with well test results, and the influence of parameters such as the half-length and permeability of supported and unsupported fractures on gas production is analyzed. Finally, the proposed method is applied to four field cases in southwest China. This paper mainly establishes an analytical method for parameter interpretation after hydraulic fracturing based on the production data analysis method considering the uneven support of fractures, which is of great significance for understanding the mechanism of fracturing stimulation, optimization of fracturing parameters, and gas production forecast.

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Gas-Production-Data Analysis of Variable-Pressure-Drawdown/Variable-Rate Systems: A Density-Based Approach

SPE Reservoir Evaluation & Engineering ◽

10.2118/172503-pa ◽

2014 ◽

Vol 17 (04) ◽

pp. 520-529 ◽

Cited By ~ 7

Author(s):

Miao Zhang ◽

Luis F. Ayala H.

Keyword(s):

Data Analysis ◽

Material Balance ◽

Gas Production ◽

Variable Pressure ◽

Production Data ◽

Variable Rate ◽

Well Performance ◽

Gas Well ◽

Type Curves ◽

Performance Forecasting

Summary This study demonstrates that production-data analysis of variable-bottomhole-flowing-pressure/variable-rate gas wells under boundary-dominated flow (BDF) is possible by use of a density-based approach. In this approach, governing equations are expressed in terms of density variables and dimensionless viscosity/compressibility ratios. Previously, the methodology was successfully used to derive rescaled exponential models for gas-rate-decline analysis of wells primarily producing at constant bottomhole pressure (Ayala and Ye 2013a, b; Ayala and Zhang 2013; Ye and Ayala 2013; Zhang and Ayala 2014). For the case of natural-gas systems experiencing BDF, gas-well-performance analysis has been made largely possible by invoking the concepts of pseudotime, normalized pseudotime, or material-balance pseudotime. The density-based methodology rigorously derived in this study, however, does not use any type of pseudotime calculations, even for variable-rate/variable-pressure-drawdown cases. The methodology enables straightforward original-gas-in-place calculations and gas-well-performance forecasting by means of type curves or straight-line analysis. A number of field and numerical case studies are presented to showcase the capabilities of the proposed approach.

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Advanced Production Data Analysis (PDA) Techniques Using Stochastic Single-Well History Matching in Coalbed Methane (CBM) Wells

10.2523/18103-ms ◽

2014 ◽

Cited By ~ 1

Author(s):

Alastair Ong ◽

Laurent Alessio ◽

Yassine Ben Salah ◽

Christopher Connell ◽

Saeed Majidaie ◽

...

Keyword(s):

Data Analysis ◽

Coalbed Methane ◽

History Matching ◽

Production Data ◽

Single Well ◽

Advanced Production

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Production Data Analysis and Practical Applications in the Sulige Tight Gas Reservoir, Ordos Basin, China

Geofluids ◽

10.1155/2021/5549725 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Minhua Cheng ◽

Wen Xue ◽

Meng Zhao ◽

Guoting Wang ◽

Bo Ning ◽

...

Keyword(s):

Data Analysis ◽

Ordos Basin ◽

Gas Production ◽

Production Data ◽

Gas Reservoirs ◽

Tight Sandstone ◽

Gas Reservoir ◽

Well Pattern ◽

Tight Gas Reservoir ◽

Wellbore Pressure

Successful exploitation of tight sandstone gas is one of the important means to ensure the “increasing reserves and production” of the oil and gas initiative and also one of the important ways to ensure national energy security. To further improve the accuracy of historical matching of field data such as gas production and bottom-hole pressure during the production process of this type of gas reservoir, in this study, a new expression of wellbore pressure for the uniform flow of vertical fractured wells in Laplace space based on the point sink function model of vertical fractures in tight sandstone gas reservoirs is constructed. This innovation is based on a typical production data analysis plot of the Blasingame type that uses the numerical inversion decoupling mathematical equation. After analyzing the pressure and pressure derivative characteristics of each flow stage in the typical curves, a new technique of type-curve matching was proposed. In order to verify the correctness of the model and the application value of the field, based on the previous production data of Sulige Gas Field in China, a new set of production data diagnostic chart of tight sandstone gas reservoir was formed. A case analysis showed that the application of the production data analysis method and data diagnosis plot in the field accurately evaluated the development effect of the tight sandstone gas reservoirs, clarified the scale of effective sand bodies, and provided technical support for optimizing and improving the well pattern and realizing the efficient development of gas fields.

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Development and Application of a Production Data Analysis Model for a Shale Gas Production Well

Fluid Dynamics & Materials Processing ◽

10.32604/fdmp.2020.08388 ◽

2020 ◽

Vol 16 (3) ◽

pp. 411-424

Author(s):

Dongkwon Han ◽

Sunil Kwon

Keyword(s):

Data Analysis ◽

Shale Gas ◽

Gas Production ◽

Production Data ◽

Analysis Model ◽

Production Well

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Advanced Production Data Analysis (PDA) Techniques Using Stochastic Single-Well History Matching in Coalbed Methane (CBM) Wells

10.2523/iptc-18103-ms ◽

2014 ◽

Cited By ~ 1

Author(s):

Alastair Ong ◽

Laurent Alessio ◽

Yassine Ben Salah ◽

Christopher Connell ◽

Saeed Majidaie ◽

...

Keyword(s):

Data Analysis ◽

Coalbed Methane ◽

History Matching ◽

Production Data ◽

Single Well ◽

Advanced Production

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An Optimization-Based Method for the Explicit Production Data Analysis of Gas Wells

Frontiers in Energy Research ◽

10.3389/fenrg.2021.801576 ◽

2022 ◽

Vol 9 ◽

Author(s):

Lixia Zhang ◽

Yong Li ◽

Xinmin Song ◽

Mingxian Wang ◽

Yang Yu ◽

...

Keyword(s):

Data Analysis ◽

Balance Equation ◽

Gas Flow ◽

Material Balance ◽

Gas Production ◽

Production Data ◽

Variable Rate ◽

Material Balance Equation ◽

Gas Wells ◽

Gas Reservoir

This work aims at the exploration of production data analysis (PDA) methods without iterations. It can overcome limitations of the advanced type curve analysis relying on the iterative calculation of material-balance pseudotime and current explicit methods reckoning on specific production schedule assumptions. The dynamic material balance equation (DMBE) is strictly proved by the integral variable substitution based on the gas flow equation under the boundary dominated flow (BDF) condition and the static material balance equation (SMBE) of a gas reservoir. We introduce the pseudopressure level function γ(p) and the recovery factor function R(p) to rewrite the DMBE in terms of observed variable Y and estimated variable Ye; then the PDA can be transformed into an optimization problem of minimizing the error between Y and Ye. An optimization-based method for the explicit production data analysis of gas wells (OBM-EPDA), therefore, is developed in the paper, capable of determining the BDF constant and gas reserves explicitly and accurately for variable rate and/or variable flowing pressure systems. Three stimulated cases demonstrate the applicability and validity of OBM-EPDA with small errors less than 1% for estimated values of both reserves and Y. Not second to previous studies, the field case analysis further proves its practicability. It is shown that the nonlinear relation of γ to R can be represented by a polynomial function merely dependent on the inherent properties of the gas production system even before sorting out the production data. The errors of observed variable Y provided by OBM-EPDA facilitate the data quality control, and the elimination of outliers not subject to the BDF condition improves the reliability of the analysis. For various gas systems producing whether at a constant rate, a constant bottomhole pressure (BHP), or under variable rate and variable BHP conditions, the proposed method gives insights into the well-controlled volume and production capacity of the gas well whether in a low-pressure or high-pressure gas reservoir, where the compressibilities of rock and bound water are considered.

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