Integrated Approach Enhances Forecasting, Reserves Estimation in Tight Gas Fields
Chris Carpenter_
This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 225006, “Unlocking Potential of Condensate-Rich Tight Gas Fields: Integrating Rate Transient Analysis and Flowing Material Balance for Enhanced Production Forecasting and Accurate Reserves Estimation,” by Ahmed E.M. Hegazy, Petronas. The paper has not been peer-reviewed.
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The primary aim of this paper is to assess the effectiveness of using advanced integrated production-data-analysis techniques for condensate-rich tight gas fields. The goal is to reduce uncertainties related to estimating hydrocarbon in place, enhance production forecasting accuracy, and improve reserves estimation. This analysis solely relies on well-production data and flowing pressures, using the rate transient analysis (RTA) and flowing material balance (FMB) techniques.
Methodology and Analysis
Application of Decline-Curve Analysis (DCA) on Tight Gas Wells.
The Arps DCA has been applied on each well of Field A (42 wells) using both spreadsheets and field-management software. The decline type adopted for all wells is hyperbolic decline (with b = 0.5), as suggested in many references for gas wells. The initial decline rate (di) was defined based on the recent production history of constant tubinghead pressure (THP) (approximately 12 bar) since last compression. Since September 2018, production rates have been in a continuous decline. Accordingly, this period has been used as a history-matching benchmark to select the representative di for each well. The range of well di is 15–30% based on historical performance of each well. The DCA was calculated in this study for 2P developed reserves [no further action (NFA) wells]. Well DCA gas-rate profiles have been summarized to obtain total field DCA, which was compared later with RTA and numerical simulation results.
Application of RTA on Tight Gas Wells.
The analytical RTA method has been applied on each well of Field A mainly to predict production profiles and reserves. RTA was performed in this study using well THP history along with gas- and oil-production-rate history. RTA was calculated here only for NFA wells. RTA was performed using Blasingame, log-log, FMB, normalized rate cumulative [Agarwal-Gardner (AG)], and Fetkovich approaches. By applying analytical RTA, the transient and pseudosteady-state (PSS) flow regimes in most of the wells were distinguished, acquiring, tabulating, and comparing all RTA results from each well.
Moreover, simple numerical models with detailed pressure/volume/temperature (PVT) and relative permeability inputs were created for only six wells from Field A in an attempt to capture the effect of condensate-dropout phenomena on well performance. The analysis also was used to compare all other RTA results from both analytical and numerical methods. By applying numerical RTA, transient and PSS flow regimes in most of the wells were distinguished, acquiring, tabulating and comparing all RTA results from each well.
The PVT and relative permeability data were even more-crucial inputs into numerical RTA modeling because of the expected condensate-banking effect. The selected RTA interpretation matched models were numerical, single-layered formation, vertical well, homogeneous reservoir, and circular boundary.