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The estimation of reserves and performance prediction are two vital tasks for the development of gas reservoirs where the evaluation of gas in place or well-controlled reserves, as the foundation of the performance analysis of gas wells, turns to be exceedingly significant. Advanced production data analysis or modern rate transient analysis (RTA) methods mainly depend on the iterative calculations of material balance quasitime ( t ca ) and type curve fitting, the essence of which is to update the average reservoir pressure data time and again. The traditional Arps’ decline models are of empirical nature despite the convenience and applicability to the constant bottomhole pressure (BHP) condition. In order to avoid the implicit iteration, this paper develops an explicit method for estimating the average reservoir pressure on the basis of dynamic material balance equation (DMBE), termed “flow integral method,” which can be applied to various gas production systems under boundary-dominated flow (BDF). Based on the flow integral method and the decline parameter evaluation, we employ the hyperbolic decline model to model the gas well performance at a constant BHP. The analytical formulations of decline rate and decline exponent are deduced from the DMBE and the static material balance equation (SMBE) considering the elastic compressibilities of rock pore and bound water. The resulting decline parameter method for explicit estimation of gas reserves boasts a solid and rigorous theory foundation that production rate, decline rate, and average reservoir pressure profiles have reference to each other, and its implementation steps are explained in the paper. The SMBE can, combined with the estimated pressure profile by the flow integral method, also be used to determine gas reserves which is not limited to the constant-BHP condition and can calibrate the estimates of the decline parameter method. The proposed methods are proven effective and reliable with several numerical cases at different BHPs and a field example.

Low permeability porous carbonate rocks occupy a certain proportion in the Middle East. Horizontal injection-production well pattern development is often adopted. Due to the influence of well type and wellbore, reservoir dynamic monitoring is mainly based on conventional daily measurement data, well test and pressure monitoring. Therefore, it is particularly important to combine well test interpretation with production dynamic analysis to diagnose the main control factors and production characteristics of this type of reservoir. In this paper, the point source function is used to obtain the pressure variation function of a horizontal well in infinite formation with upper and lower closed boundary. The difference between the horizontal well test curve of A reservoir and the typical horizontal well test curve is compared and analyzed, and the abnormal well test curve of horizontal wells is characterized by a linear flow phase with a slope of 1/3 or 1/4. The abnormal well test curve accounted for 33.34%. The main influencing factors are the permeability around the well and the well trajectory. By combining well test interpretation with dynamic inversion method, the correlation between well test interpretation and dynamic characteristics of horizontal wells with different characteristics is classified and clarified. The main controlling factors that affect the difference in the water injection development effect of different horizontal wells are further clarified, and provide an important reference for the adjustment of injection-production parameters and the optimal deployment of schemes.

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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