Production data analysis of unconventional gas wells: Review of theory and best practices

Abstract Unconventional gas reservoirs, including coalbed methane (CBM), tight gas (TG) and shale gas (SG), have become a significant source of hydrocarbon supply in North America, and interest in these resource plays has been generated globally. Despite a growing exploitation history, there is still much to be learned about fluid storage and transport properties of these reservoirs. A key task of petroleum engineers and geoscientists is to use historical production (reservoir fluid production rate histories, and cumulative production) for the purposes of 1) reservoir and well stimulation characterization and 2) production forecasting for reserve estimation and development planning. Both of these subtasks fall within the domain of quantitative production data analysis (PDA). PDA can be performed analytically, where physical models are applied to historical production and flowing pressure data to first extract information about the reservoir (i.e. hydrocarbon-in-place, permeability-thickness product) and stimulation (i.e. skin or hydraulic fracture properties) and then generate a forecast using a model that has been “calibrated” to the dynamic data (i.e. rates and pressures). Analytical production data analysis methods, often referred to as rate-transient analysis (RTA), utilize concepts analogous to pressure-transient analysis (PTA) for their implementation, and hence have a firm grounding in the physics of fluid storage and flow. Empirical methods, such as decline curve analysis, rely on empirical curve fits to historical production data, and projections to the future. These methods do not rigorously account for dynamic changes in well operating conditions (i.e. flowing pressures), or reservoir or fluid property changes. Quantitative PDA is now routinely applied for conventional reservoirs, where the physics of fluid storage and flow are relatively well-understood. RTA has evolved extensively over the past four decades, and empirical methods are now applied with constraints and “rules of thumb” developed by researchers with some confidence. For unconventional reservoirs, these techniques continue to evolve according to our improved understanding of the physics of fluid storage and flow. In this article, the latest techniques for quantitative PDA including type-curve analysis, straight-line (flow-regime) analysis, analytical and numerical simulation and empirical methods are briefly reviewed, specifically addressing their adaptation for CBM and SG reservoirs. Simulated and field examples are provided to demonstrate application. It is hoped that this article will serve as practical guide to production analysis for unconventional reservoirs as well as reveal the latest advances in these techniques.