The Choke as a Brainbox for Smart Wellhead Control

Stanley I. Okafor, Azubuike H. Amadi, Mobolaji A. Abegunde and Joseph A. Ajienka

European Journal of Engineering and Technology Research, 2021, vol. 6, issue 1, 114-118

Abstract: This project uses production data to generate well-specific correlations for GLR, BSW and sand concentration which are used for predictions. A software has been developed to effect a smart control algorithm. This results in a bean up or bean down operation depending on the current flowing conditions and constraints. Excel programming environment was used to write a code that constantly takes in measured data points, models the behavior of the individual data sets with bean size and controls the choke if the parameters of interest go above a predetermined cut-off. The software was also equipped with an inverse matrix solving algorithm that enables it to determine the choke performance constants for any set of initialization data. A set of data from field X were supplied and the choke performance constants; A, B, C, D and E, were found to be 10, 0.546, 0.0, 1.89 and 1.0 respectively. In addition to that, data from subsequent production operations were entered and the software was able to control the choke size to ensure that production stays below set constraints of 500, 80 and 10 in field units for GLR, BSW and sand concentration respectively. From this, it can be concluded that the software can effectively maintain the production of unwanted well effluents below their cut-offs, thereby improving oil production and the overall Net Profit Value (NPV) of a project.

Keywords: Algorithm; Choke Performance; Smart Control; Well problems; Multiphase flow (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:epw:ejeng0:v:6:y:2021:i:1:id:62346

DOI: 10.24018/ejeng.2021.6.1.2346

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