The Evaluation and Sensitivity of Decline Curve Modelling

Prinisha Manda and Diakanua Bavon Nkazi
Additional contact information
Prinisha Manda: Oil and Gas Production and Processing Research Unit, School of Chemical and Metallurgical Engineering, University of the Witwatersrand, Johannesburg 2000, South Africa
Diakanua Bavon Nkazi: Oil and Gas Production and Processing Research Unit, School of Chemical and Metallurgical Engineering, University of the Witwatersrand, Johannesburg 2000, South Africa

Energies, 2020, vol. 13, issue 11, 1-16

Abstract: The development of prediction tools for production performance and the lifespan of shale gas reservoirs has been a focus for petroleum engineers. Several decline curve models have been developed and compared with data from shale gas production. To accurately forecast the estimated ultimate recovery for shale gas reservoirs, consistent and accurate decline curve modelling is required. In this paper, the current decline curve models are evaluated using the goodness of fit as a measure of accuracy with field data. The evaluation found that there are advantages in using the current DCA models; however, they also have limitations associated with them that have to be addressed. Based on the accuracy assessment conducted on the different models, it appears that the Stretched Exponential Decline Model (SEDM) and Logistic Growth Model (LGM), followed by the Extended Exponential Decline Model (EEDM), the Power Law Exponential Model (PLE), the Doung’s Model, and lastly, the Arps Hyperbolic Decline Model, provide the best fit with production data.

Keywords: valuation; shale gas reservoirs (SGR); decline curve models; decline curve analysis (DCA); estimated ultimate recovery (EUR) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/1996-1073/13/11/2765/pdf (application/pdf)
https://www.mdpi.com/1996-1073/13/11/2765/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:11:p:2765-:d:365647

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().