Rate Decline-based Models for Gas Reservoir Performance Prediction in Niger Delta Region

Okon, Anietie and Olagunju, Daniel and Akpabio, Julius (2017) Rate Decline-based Models for Gas Reservoir Performance Prediction in Niger Delta Region. British Journal of Applied Science & Technology, 19 (1). pp. 1-14. ISSN 22310843

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Abstract

This work considers the Decline Curve Analysis (DCA) approach as a quick tool to estimate the gas reservoir performance of field “ABC” in the Niger Delta region. The conventional Arps’ models: Exponential, Harmonic and Hyperbolic, alongside with the Reciprocal and Quadratic models were used. Production data: gas production rate (qt) and gas cumulative production (GP) were obtained from 13 wells in the field “ABC”. Multivariate analyses were performed with the mentioned models to establish the decline constant (Di) and decline exponent (b); for hyperbolic model, of the field “ABC” in the Niger Delta region. A decline constant of 0.000064day-1 was obtained from all the models with exception of Reciprocal model with 0.00053day-1 for the gas field. Also, the decline exponent (b) obtained for Hyperbolic model was 0.9999. The statistical analysis: absolute error, standard deviation and coefficient of determination, of the fitted models used to ascertain the extent of their predicted values differ from the field test data results in Arps’ models: Exponential - 0.1150, 0.02666 and 0.9981; Harmonic - 0.11547, 0.02665 and 0.9982 and Hyperbolic - 0.11547, 0.02665 and 0.9982, respectively. Furthermore, Reciprocal and Quadratic models generated an absolute error, standard deviation and coefficient of determination of 0.09726, 0.026745 and 0.9911, and 0.0097, 0.000008 and 0.9998, respectively. Thus, the results indicate that, modern rate decline models for reservoir performance analysis can compete with the well-known Arps’ model(s). Therefore, the fitted Quadratic-based model can be used as a quick tool to analyze the reservoir performance of the gas field “ABC” in the Niger Delta region.

Item Type: Article
Subjects: OA Open Library > Multidisciplinary
Depositing User: Unnamed user with email support@oaopenlibrary.com
Date Deposited: 22 May 2023 05:42
Last Modified: 31 Jan 2024 04:02
URI: http://archive.sdpublishers.com/id/eprint/717

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