Excess pore pressure behavior and evolution in deep coalbed methane reservoirs

Deep coalbed methane(DCBM),an unconventional gas reservoir,has undergone significant advancements in recent years,sparking a growing interest in assessing pore pressure dynamics within these reservoirs.While some production data analysis techniques have been adapted from conventional oil and gas wells,there remains a gap in the understanding of pore pressure generation and evolution,particularly in wells subjected to large-scale hydraulic fracturing.To address this gap,a novel technique called excess pore pressure analysis(EPPA)has been introduced to the coal seam gas industry for the first time to our knowledge,which employs dual-phase flow principles based on consolidation theory.This technique focuses on the generation and dissipation for excess pore-water pressure(EPWP)and excess pore-gas pressure(EPGP)in stimulated deep coal reservoirs.Equations have been developed respectively and numerical solutions have been provided using the finite element method(FEM).Application of this model to a representative field example reveals that excess pore pressure arises from rapid loading,with overburden weight transferred under undrained condition due to intense hydraulic fracturing,which significantly redistributes the weight-bearing role from the solid coal structure to the injected fluid and liberated gas within artificial pores over a brief timespan.Furthermore,field application indicates that the dissipation of EPWP and EPGP can be actually considered as the process of well production,where methane and water are extracted from deep coalbed methane wells,leading to consolidation for the artificial reservoirs.Moreover,history matching results demonstrate that the excess-pressure model established in this study provides a better explanation for the declining trends observed in both gas and water production curves,compared to conventional practices in coalbed methane reservoir engineering and petroleum engineering.This research not only enhances the understanding of DCBM reservoir behavior but also offers insights applicable to production analysis in other unconventional resources reliant on hydraulic fracturing.

An improved data space inversion method to predict reservoir state fields via observed production data

A data-space inversion(DSI)method has been recently proposed and successfully applied to the history matching and production prediction of reservoirs.Based on Bayesian theory,DSI can directly and effectively obtain good posterior flow predictions without inversion of geological parameters of reservoir model.This paper presents an improved DSI method to fast predict reservoir state fields(e.g.saturation and pressure profiles)via observed production data.Firstly,a large number of production curves and state data are generated by reservoir model simulation to expand the data space of original DSI.Then,efficient history matching only on the observed production data is carried out via the original DSI to obtain related parameters which reflects the weight of the real reservoir model relative to prior reservoir models.Finally,those parameters are used to predict the oil saturation and pressure profiles of the real reservoir model by combining large amounts of state data of prior reservoir models.Two examples including conventional heterogeneous and unconventional fractured reservoir are implemented to test the performances of predicting saturation and pressure profiles of this improved DSI method.Besides,this method is also tested in a real field and the obtained results show the high computational efficiency and high accuracy of the practical application of this method.

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

This paper presents the development and application of a production data analysis software that can analyze and forecast the production performance and reservoir properties of shale gas wells.The theories used in the study were based on the analytical and empirical approaches.Its reliability has been confirmed through comparisons with a commercial software.Using transient data relating to multi-stage hydraulic fractured horizontal wells,it was confirmed that the accuracy of the modified hyperbolic method showed an error of approximately 4%compared to the actual estimated ultimate recovery(EUR).On the basis of the developed model,reliable productivity forecasts have been obtained by analyzing field production data relating to wells in Canada.The EUR was computed as 9.6 Bcf using the modified hyperbolic method.Employing the Pow Law Exponential method,the EUR would be 9.4 Bcf.The models developed in this study will allow in the future integration of new analytical and empirical theories in a relatively readily than commercial models.

Data as a Factor of Production Promoting the Deep Integration of the Digital Economy and the Real Economy:Theoretical Logic and Analysis Framework

Data is the primary factor of production in the digital economy,playing a role in promoting the deep integration of the digital economy and the real economy and smoothing the national economic cycle.After entering the circulation system of the real economy,data is rapidly integrated into production,circulation,consumption,distribution,and other links.It optimizes resource allocation,unblocks circulation channels,promotes accurate matching of supply and demand,stimulates emerging demand,and forms a virtuous circle of digital technology application,traditional physical enterprise transformation,and technological innovation.Integrated development is an important feature of the digital economy.Data promotes the integration of factors of production,products,enterprises,industries,and markets,which fosters a circular system with deep integration of the digital economy and the real economy.To promote the deep integration of the digital economy and the real economy,the government and business entities should take measures to improve the circular efficiency of the digital economy and the real economy.These measures include attaching importance to the role of data-driven development,improving data capacity,data development,and utilization in enterprises,exploring diverse circulation models of enterprise data,and creating typical application scenarios and industrial data spaces.

Study of inter-well interference in shale gas reservoirs by a robust production data analysis method based on deconvolution

In order to overcome the defects that the analysis of multi-well typical curves of shale gas reservoirs is rarely applied to engineering,this study proposes a robust production data analysis method based on deconvolution,which is used for multi-well inter-well interference research.In this study,a multi-well conceptual trilinear seepage model for multi-stage fractured horizontal wells was established,and its Laplace solutions under two different outer boundary conditions were obtained.Then,an improved pressure deconvolution algorithm was used to normalize the scattered production data.Furthermore,the typical curve fitting was carried out using the production data and the seepage model solution.Finally,some reservoir parameters and fracturing parameters were interpreted,and the intensity of inter-well interference was compared.The effectiveness of the method was verified by analyzing the production dynamic data of six shale gas wells in Duvernay area.The results showed that the fitting effect of typical curves was greatly improved due to the mutual restriction between deconvolution calculation parameter debugging and seepage model parameter debugging.Besides,by using the morphological characteristics of the log-log typical curves and the time corresponding to the intersection point of the log-log typical curves of two models under different outer boundary conditions,the strength of the interference between wells on the same well platform was well judged.This work can provide a reference for the optimization of well spacing and hydraulic fracturing measures for shale gas wells.

Maximizing the Benefit of Rate Transient Analysis for Gas Condensate Reservoirs

In recent years,many trials have been made to use the Rate Transient Analysis(RTA)techniques as a method to describe the gas condensate reservoirs.The problem with using these techniques is the multi-phase behavior of the gas condensate reservoirs.Therefore,the Pressure Transient Analysis(PTA)is commonly used in this case to analyze the reservoir parameters.In this paper,we are going to compare the results of both PTA and RTA of three wells in gas condensate reservoirs.The comparison showed a great match between the results of the two mentioned techniques for the first time using a reference GOR of 75,000 SCF/STB.Therefore,we concluded that we could depend on RTA instead of PTA to spare the cost associated with the PTA in the gas condensate reservoirs.