Abstract Accurate reserves evaluation is essential across all reservoir types, as it underpins effective development planning, informed investment decisions, and optimized field performance throughout the asset lifecycle. However, in unconventional reservoirs, ultra-low permeability, nonlinear flow behavior, and the presence of multiple gas storage mechanisms pose significant challenges to the reliability and applicability of conventional methods. This paper presents a novel flowing material balance (FMB) approach tailored for such reservoirs and compares it with various existing FMB-based techniques. A practical field case study is used to demonstrate how this semi-analytical workflow simplifies reserves estimation and maintains coherence with other established methods. This methodology utilizes the Jensen-Smith Static Material Balance by incorporating dynamic production data and flowing pressure, eliminating the need for complex average reservoir pressure measurements. Isotherm-based sorption models are integrated with phase- specific productivity indices to develop a practical flowing material balance (FMB) framework suitable for field application. Applied to coalbed methane data with dual-porosity and high sorption capacity, the approach is validated using diagnostics such as P-Q plots, Normalized Gas Potential (NGP), Material Balance Time (MBT), the Normalized Rate-Cumulative Generalized FMB method, and other standard techniques, followed by analytical forecasting under various sensitivity scenarios. The proposed flowing material balance (FMB) methodology demonstrated a significantly improved match between estimated and actual connected gas-in-place (GIP) in coalbed methane reservoirs with dominant sorbed gas storage. Multiple blind-tests and sensitivity analyses confirmed the method's robustness across varying reservoir conditions. By integrating sorption dynamics and flowing pressure into the FMB framework, the model effectively captured both early transient behaviour and late-time boundary-dominated flow, improving the reliability of reserves estimation. Comparative results showed connected GIP estimates within engineering margin of those obtained from King's method and the Generalized FMB, demonstrating consistency and validating methodological soundness. Field application confirmed its capability to characterize dynamic drainage areas, identify flow regimes, and assess well productivity trends with greater precision. Additionally, the methodology provided improved insight into completion efficiency and depletion patterns, facilitating more informed decisions around well spacing, stimulation design, and asset development planning.
Shubham Patel (Mon,) studied this question.
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