From Flow Regimes to Reserves: A General Type Curve for Shale Gas Using Modern Rate-Time Analysis

Abstract This work presents a type curve—based on flow regimes—for assessing remaining reserves in unconventional tight gas reservoirs (shale gas). Unlike decline curve modeling, type curves can be universally used across the lease, region, and/or basin that reduces to a minimum the subjectivity of empirical decline curves. We include a discussion on the advantage of defining type-curve from decline-curve analysis. Moreover, as Michael J. Fetkovitch (1980) originally intended to, this work expands on assessing flow regimes (transient flow, boundary dominated flow, and exterior flow) before performing a forecast. By introducing the Normalized Cumulative Type Curve: which plots normalized cumulative gas production versus material balance time (MBT), it reveals a "fingerprint" of shale gas production that enables a better assessment of flow regimes and remaining reserves. Afterwards, any decline curve model can be used. This work also attempts to solve the existing challenge of reserves categorization of shale gas production in SPE PRMS 2018 guidelines, which currently do not account for shale gas reserves categorization. By redefining how we evaluate reserves and improving the accuracy of forecasts of this resource, we intend to address a solution for the current vagueness of SPE-PRMS. Based on the evidence presented, we propose that future volumes from subsequent flow regimes (e.g. exterior flow) could be categorized as Probable (P2) Reserves while the volumes in the current flow regime (e.g. boundary-dominated flow) are categorized as Proved (P1). This suggestion is solely based on addressing the uncertainty of late-time production behavior. Results are validated using production data from the Haynesville Shale, where high pressure drawdowns allow the manifestation of exterior flow earlier than in other basins. The absolute error of estimating remaining reserves using the Normalized Cumulative method compared to a classic decline-curve plot of rate vs. cumulative, is less than 1%. Similar results are observed in Marcellus Shale and regions where over-pressure is present, though other basins are yet to be evaluated. The advantage of using this method, however, is that it operates as diagnostic to universal behavior for shale gas production—reducing uncertainties despite completion strategies, local geology, fracture geometries, operators, etc. The method can become a diagnostic tool across operators useful for estimation of remaining reserves, especially when using publicly-available data (which ultimately is rate and time). By reducing the uncertainty of forecasts and suggesting categorization of this resource, the method proposed could have important implications for shale-gas reserves. Should the reserves community adopt it, it may be proposed as part of the next update of PRMS Guidelines.

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Journal
SPE Annual Technical Conference and Exhibition
Published
2025-10-13
DOI
https://doi.org/10.2118/228157-ms
Primary Topic
Reservoir Engineering and Simulation Methods
Type
article
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article

From Flow Regimes to Reserves: A General Type Curve for Shale Gas Using Modern Rate-Time Analysis

David A. DiCarlo, Frank Male, Larry W. Lake, Julio C. Villarroel
SPE Annual Technical Conference and Exhibition
Reservoir Engineering and Simulation Methods
article

From Flow Regimes to Reserves: A General Type Curve for Shale Gas Using Modern Rate-Time Analysis

David A. DiCarlo, Frank Male, Larry W. Lake, Julio C. Villarroel
article en

Abstract

Abstract This work presents a type curve—based on flow regimes—for assessing remaining reserves in unconventional tight gas reservoirs (shale gas). Unlike decline curve modeling, type curves can be universally used across the lease, region, and/or basin that reduces to a minimum the subjectivity of empirical decline curves. We include a discussion on the advantage of defining type-curve from decline-curve analysis. Moreover, as Michael J. Fetkovitch (1980) originally intended to, this work expands on assessing flow regimes (transient flow, boundary dominated flow, and exterior flow) before performing a forecast. By introducing the Normalized Cumulative Type Curve: which plots normalized cumulative gas production versus material balance time (MBT), it reveals a "fingerprint" of shale gas production that enables a better assessment of flow regimes and remaining reserves. Afterwards, any decline curve model can be used. This work also attempts to solve the existing challenge of reserves categorization of shale gas production in SPE PRMS 2018 guidelines, which currently do not account for shale gas reserves categorization. By redefining how we evaluate reserves and improving the accuracy of forecasts of this resource, we intend to address a solution for the current vagueness of SPE-PRMS. Based on the evidence presented, we propose that future volumes from subsequent flow regimes (e.g. exterior flow) could be categorized as Probable (P2) Reserves while the volumes in the current flow regime (e.g. boundary-dominated flow) are categorized as Proved (P1). This suggestion is solely based on addressing the uncertainty of late-time production behavior. Results are validated using production data from the Haynesville Shale, where high pressure drawdowns allow the manifestation of exterior flow earlier than in other basins. The absolute error of estimating remaining reserves using the Normalized Cumulative method compared to a classic decline-curve plot of rate vs. cumulative, is less than 1%. Similar results are observed in Marcellus Shale and regions where over-pressure is present, though other basins are yet to be evaluated. The advantage of using this method, however, is that it operates as diagnostic to universal behavior for shale gas production—reducing uncertainties despite completion strategies, local geology, fracture geometries, operators, etc. The method can become a diagnostic tool across operators useful for estimation of remaining reserves, especially when using publicly-available data (which ultimately is rate and time). By reducing the uncertainty of forecasts and suggesting categorization of this resource, the method proposed could have important implications for shale-gas reserves. Should the reserves community adopt it, it may be proposed as part of the next update of PRMS Guidelines.

SPE Annual Technical Conference and Exhibition
Pennsylvania State University (US), The University of Texas at Austin (US)
Openalex Percentile: Top 36%
Reservoir Engineering and Simulation Methods
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