Search

Designing drilling mud rheology is a complex task, particularly when it comes to preventing filter cakes from obstructing formation pores and making sure they can be easily decomposed using breakers. Incorporating both multiphysics and data-driven numerical simulations into the design of mud rheology experiments creates an additional challenge due to their symmetrical integration. In this computational intelligence study, we introduced numerical validation techniques using 498 available datasets from mud rheology and images from filter cakes. The goal was to symmetrically predict flow, maximize filtration volume, monitor void spaces, and evaluate formation damage occurrences. A neural-objective and image optimization approach to drilling mud rheology automation was employed using an artificial neural network feedforward (ANN-FF) function, a non-ANN-FF function, an image processing tool, and an objective optimization tool. These methods utilized the Google TensorFlow Sequential API-DNN architecture, MATLAB-nftool, the MATLAB-image processing tool, and a single-objective optimization algorithm. However, the analysis emanating from the ANN-FF and non-ANN-FF (with neurons of 10, 12, and 18) indicated that, unlike non-ANN-FF, ANN-FF obtained the highest correlation coefficient of 0.96–0.99. Also, the analysis of SBM and OBM image processing revealed a total void area of 1790 M µm2 and 1739 M µm2, respectively. Both SBM and OBM exhibited notable porosity and permeability that contributed to the enhancement of the flow index. Nonetheless, this study did reveal that the experimental-informed single objective analysis impeded the filtration volume; hence, it demonstrated potential formation damage. It is, therefore, consistent to note that automating flow predictions from mud rheology and filter cakes present an alternative intelligence method for non-programmers to optimize drilling productive time. [ABSTRACT FROM AUTHOR]

Abstract This study reports the extraction and performance evaluation of two bio-derived polymers for enhanced oil recovery applications. The oil displacement processes were conducted using six (6) unconsolidated sandstone core plugs. Reservoir permeability tester was used to simulate real reservoir conditions in order to evaluate the suitability of the formulated biopolymers for oil displacement applications at laboratory conditions. The experimental results indicate the effectiveness of the biopolymer solutions in enhanced oil recovery in terms of their superior incremental oil recoveries after conventional waterflood with percentage oil recovery of 30.9–39.3% for banana peel derived polymer and 40.6–50.8% for mango kernel derived polymer compared to conventional waterflood with percentage recovery of 16.2–32% of the initial oil in place. This work identified the potential suitability and use of bio-derived polymers for enhanced oil recovery applications with emphasis on their biodegradability.

The impact of neglected well bore pressure losses due to fluid accumulation and kinetic energy in the fundamental energy equation used for derivation of flowing bottom-hole pressure in horizontal well have been conceived to be a considerable reason for the discrepancy between computed rates from the existing models and actual rates got from production tests. In the study, a new model that investigate all possible well bore pressure losses effect on the production rate of a horizontal oil well have been established. The newly developed model has been validated using the field data obtained from the literature and outcome got from the new model yields more satisfactory results. A more realistic results that evident all flow phenomena in petroleum production well include the initial unsteady, pseudo-steady and steady state flow condition hence flow rate at any given production time has been established for flow of oil along horizontal production well. The concept is useful to estimate flowing bottom-hole pressure and analyze its effect on production rate value of a horizontal oil well without ignoring any pressure resisting terms in the governing thermodynamic equation. The unsteadiness fluid flow period that generally observed after shut in a well have also been demonstrated. Closer agreement between the results obtained using the newly developed model and real life field measurement was observed when compared with the previous model in the literature. The study gives reservoir engineer an exact and helpful device for estimating and assessing horizontal oil well production rate.