The Use of Linear Least Squares Regression Method (LLSRM) for Estimating Petroleum Reserves in Niger Delta Region of Nigeria
Oseh, J. O., Oguamah, I. A., Ogunkunle, F.T.
Corresponding Author : Oseh, J. O,
Department of Chemical and Petroleum Engineering, Afe Babalola University, Ado â€“ Ekiti (ABUAD), Nigeria.
Email ID : firstname.lastname@example.org
Received : 2014-11-14 Accepted : 2014-12-29 Published : 2014-12-29
Abstract : Hydrocarbon reserves are basic to planning and investment decisions in Petroleum Industry. Therefore its proper estimation is of considerable importance in oil and gas production. The estimation of hydrocarbon reserves in the Niger Delta Region of Nigeria has been very popular, and very successful, in the Nigerian oil and gas industry for the past 50 years. In order to fully estimate the hydrocarbon potentials in Nigerian Niger Delta Region, a clear understanding of the reserve geology and production history should be acknowledged. Reserves estimation of most fields is often performed through Material Balance and Volumetric methods. Alternatively a simple Estimation Model and Least Squares Regression may be useful or appropriate. This model is based on extrapolation of additional reserve due to exploratory drilling trend and the additional reserve factor which is due to revision of the existing fields. The Estimation Model and the Linear Regression Analysis used in this study gives improved estimates of the fields considered, hence can be used in other Nigerian Fields with recent production history.
Keywords : Petroleum Reserves, Estimation Model, Linear Least Squares Regression Method, Niger Delta, Estimated Reserves, Actual Reserves.
Citation : Oseh, J. O. et all., (2014) The Use of Linear Least Squares Regression Method (LLSRM) for Estimating Petroleum Reserves in Niger Delta Region of Nigeria. J. of Advancement in Engineering and Technology. V2I2. DOI : 10.5281/zenodo.898017
Copyright : © 2014 Oseh, J. O. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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