Empirical Wellhead Pressure-Production Rate Correlations for Niger Delta Oil Wells

Abstract

Several correlations have been developed to predict wellhead pressure–production rate relationship in the Niger Delta region. Regrettably, most of these correlations were developed from field data that are not from the Niger Delta region and with limited field test data ranges, so their predictions are lower than expected field values when applied to the Niger Delta. Additionally, some developed wellhead pressure–production rate correlations based on Niger Delta field data are made using in-house equations by the operating companies in the Niger Delta region. To ameliorate this anomaly, sixty four (64) field test data: choke size (S), production rate (q), gas-liquid ratio (GLR), flowing wellhead pressure (Pwh), flowing temperature (FTHP) and basic sediment and water (BS&W) were collected from oil producing wells in the Niger Delta region to develop wellhead pressure–production rate correlations based on Gilbert correlation and modified Gilbert equations. The developed correlations using Niger Delta field test data were compared with several authors' correlations. The results obtained indicate that the developed correlations resulted in better predictions than earlier correlations. In addition, the statistical analysis of the developed correlations used to ascertain the extent of their predicted values differ from the field test data and resulted in average error, absolute error and standard deviation of −0.1477, 0.4430 and 0.9582 for Gilbert formula and −0.2515, 0.4737 and 1.0997 for modified Gilbert formula, respectively. Furthermore, the developed correlations are comparable with an average correlation coefficient of 0.9869. Therefore, the developed correlations can be used as a quick tool to estimate the wellhead pressure–production rate relationship in Niger Delta oil fields.

Mathematical and Kinetic Modelling for Convective Hot Air Drying of Sweet Potatoes (<i>Ipomoea batatas L</i>)

“…The variables o α through 2 α could be determined iteratively using multivariable numerical optimization method. To determine these variables, existing literature indicates that, there are several approaches to performing this iterative estimation, namely, Gauss-Newton, the Marquardt-Levenberg, the Nelder-Mead, the steepest descent, General Reduced Gradient (GRG) protocol [23][24][25][26].…”

Integrated-reservoir-model-based critical oil rate correlation for vertical wells in thin oil rim reservoirs in the Niger Delta

“…Where bo is coefficient (i.e., proportionality constant) and β1 through β9 are exponential constants for the critical oil variables. In the Equation 12, the bo and coefficients β1 through β9 were determined iteratively using multivariable numerical optimization. In the literature, there are several approaches to perform this iterative estimation, namely, Gauss-Newton, the Marquardt-Levenberg, the Nelder-Mead, the steepest descent, etc.…”

“…[17][18][19]. Okon et al [12] mentioned that there is a robust and reliable Solver in Microsoft Excel, which uses General Reduced Gradient (GRG) as the iterative algorithm that can be used to perform multivariable numerical solution. Thence, the reservoir, fluid and well completion parameters required to determine the coefficient (bo) and exponential constants (β1 through β9) in the Equation 11 were obtained from the ADX Oilfield production data (Table 1).…”

“…Consequently, this approach does not consider the heterogeneity nature of the reservoirs. Hence, it leaves these available correlations in doubt, considering the sensitive nature of thin oil rim reservoirs [12][13]. Besides, there are correlations based on data obtained from other oil producing regions of the World.…”

Correlation for Predicting Water Breakthrough Time in Thin Oil Rim Reservoirs in the Niger Delta

“…(Wei, 2013;Smyth, 2015;Pashaie et al, 2016;among others). Okon et al (2015) added that there is a robust and reliable Solver in Microsoft Excel which uses General Reduced Gradient (GRG) as the iterative protocol that can be used to perform multivariable numerical solution.…”