Applications of Material Balance Technique in Tight Gas Reservoirs: A Systematic Literature Review

Material balance is a widely utilized analytical method in hydrocarbon exploration and production. However, its application to tight gas reservoirs (TGRs) presents significant challenges due to their low permeability and complex flow behavior. Key issues include difficulties in assessing permeability and pressure, which complicate the estimation of original gas in place (OGIP) and reserves. This review article highlights the challenges of obtaining accurate reservoir pressure data, a critical component for effective material balance studies. It discusses the inherent complexities of reservoir performance that further complicate data interpretation. This review article discusses adaptations and innovations in material balance methods developed to meet these challenges. Dynamic Material Balance – it allows real-time data to better understand the behavior of the reservoir without needing to shut-in the wells. It performs a small dynamic analysis of well data, a very important part of this assessment. More specifically, these attributes benefit TGRs, where traditional approaches struggle. This review highlights the main aspects and uses of dynamic material balance methods in TGRs, demonstrating their ability to enhance reserves assessment and economic viability. The focus later turns to adaptations and innovations of material balance techniques that can be employed to overcome these challenges. Dynamic material balance is a key area developed using real-time data, offering a better understanding of reservoir behavior without shutting a well. It is especially helpful in TGRs, where conventional approaches can lack effectiveness. The review describes important aspects and applications of dynamic material balance approaches to TGRs, showcasing their potential for improving reserve estimates and the economics of reserve recovery. The paper also promotes a more compartmented reservoir model, which is shown better to represent the actual behavior of tight gas reservoirs. This enabling model’s evolution significantly predicts OGIP and UR factors better by overcoming the complexities of tight gas behavior. Overall, this review highlights that the presented methods have good accuracy in gas volume and pressure calculations, are validated for TGRs, and are helpful for improved reservoir management decisions.