A New analytical Model for Production Data Analysis in Horizontal Wells of Tight Gas Reservoirs

Abstract

Abstract The evaluation of estimated ultimate recovery (EUR) in tight gas reservoirs holds paramount significance within the domain of unconventional oil and gas development. However, the accuracy of EUR prediction using traditional decline models is hampered by the complexity of the percolation environment after the compaction of tight sandstone and the limitations of commonly employed models. This paper proposes a new and rapid EUR evaluation method for tight gas reservoirs based on production data analysis (PDA). First, an improved model is utilized to fit the production dynamic history, enabling the determination of reservoir and fracture parameters. The introduction of the rate-normalized pressure (RNP) technique reduces the occurrence of multiple solutions during parameter inversion, simplifies the calculation of the linear flow parameter [(LFP= total fracture area × square root of permeability)], and facilitates the estimation of EUR through productivity simulation. Secondly, to validate the reliability of the proposed method, an application analysis is conducted using the Sulige gas field as a case study. The results demonstrate that the LFP and EUR of the JA well are 1196.09 m2·md0.5 and 3.17×107 m3, respectively. Furthermore, the EUR range of four representative wells is examined, revealing an actual range of 1.98×107 m3 to 4.77×107 m3, while the EUR range obtained through linear analysis is 2.00×107 m3 to 5.07×107 m3, with relative errors of 1.10%, 3.50%, 6.30%, and 1.05%, respectively. The average error remains within 5%. Additionally, correlation analysis conducted with over ten typical wells confirms a positive correlation LFP with EUR. In conclusion, this paper presents a novel and efficient methodology approach for predicting production and estimating ultimate recoveries in shale gas wells. By overcoming the limitations of traditional decline models, the proposed method offers improved accuracy and reliability in EUR evaluation. These findings enhance our understanding of EUR estimation in tight gas reservoirs and contribute to informed decision-making in the development of these valuable energy resources.