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Keywords: neural network
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Proceedings Papers

Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 1–3, 2022
Paper Number: SPE-211987-MS
...Abstract Abstract This study attempts to estimate permeability from well logs data and also predict values from existing rock sections to points that are missing using Artificial Neural Network (ANN) and Sequential Gaussian Simulation (SGS). Potentially, exploration data is prone to trends...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 1–3, 2022
Paper Number: SPE-212016-MS
... of determination of 0.989% after GA optimization. artificial intelligence rop upstream oil & gas evolutionary algorithm dataset artificial neural network genetic algorithm neural network machine learning prediction correlation drilling driven model algorithm accuracy optimization algorithm...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 1–3, 2022
Paper Number: SPE-212018-MS
... the process. As a tilt from the conventional methodology of forecasting involving use of curve fitting techniques, and multi-level computational analysis, data driven approaches can be employed. This study presents the applications of data driven approaches to forecast production. Deep learning neural network...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 1–3, 2022
Paper Number: SPE-212019-MS
... of classifying the lithology. lithology upstream oil & gas reservoir characterization neural network artificial intelligence prediction algorithm structural geology machine learning identification classification optimized supervised machine learning algorithm clustering classifier support...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 1–3, 2022
Paper Number: SPE-212028-MS
...Abstract Abstract Subsurface numerical models take a significant time to build and run. For this reason, the energy industry has been looking towards proxy models that could reduce model computational time. With the advancement of artificial neural network algorithms, building proxy models has...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 1–3, 2022
Paper Number: SPE-211926-MS
.... Python programming language environment using Tensorflow and Keras deep learning libraries with early stopping to prevent overfitting and inaccuracy was implemented. The approach was based on a three-layered supervised deep neural network developed as a function of pipe diameter, pipe inclination, fluid...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 1–3, 2022
Paper Number: SPE-211941-MS
..., Machine Learning has been applied in the study of fluid flow both in porous media and pipelines. In this work, Artificial Neural Network (ANN) is applied in the development of drift velocity closure relationship for multiphase flow models. The model is trained using some input parameters: pipe internal...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 1–3, 2022
Paper Number: SPE-211956-MS
... of this paper is to present the application of a machine learning-based framework to predict the future performance of producing wells in some reservoirs in Niger Delta. In this paper, a machine learning model (Neural Networks model) was used to detect the non-linear relationship between the inputs...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 1–3, 2022
Paper Number: SPE-211968-MS
... non-linear regression (MNLR), neural network (NN), support vector machine (SVM), and the group method of data handling (GMDH) techniques were used to develop several correlations. Results show that the GMDH method yielded the best correlation while the MNLR is the least accurate. The root means square...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 1–3, 2022
Paper Number: SPE-211979-MS
... for the purpose of accurately predicting monthly natural gas spot prices. Henry Hub natural gas spot price data from January 2001 to November 2021 were utilized alongside four machine learning algorithms namely; Artificial Neural Networks (ANN), Support Vector Regression (SVR), Random Forest Regressor...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 1–3, 2022
Paper Number: SPE-212000-MS
... flow assurance flowrate experiment algorithm temperature prediction neural network machine learning plot molecule gas-dominated system regression pressure ridge regression pipeline evaluation artificial intelligence hydrate dataset hydrate risk management cross-correlation plot...
Proceedings Papers

Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 2–4, 2021
Paper Number: SPE-207193-MS
...-learning algorithm to predict sanding in sandstone formations. A two-layered Artificial Neural Network (ANN) with back-propagation algorithm was developed using PYTHON programming language. The algorithm uses 11 geological and reservoir parameters that are associated with the onset of sanding...
Proceedings Papers

Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 2–4, 2021
Paper Number: SPE-208451-MS
... to embrace the use of novel technologies and artificial intelligence in its bid to be sustainable which is why this study focuses on the use of artificial intelligent models in predicting the rate of penetration. The predictive performance of three data-driven models [artificial neural network (ANN), extreme...
Proceedings Papers

Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 2–4, 2021
Paper Number: SPE-208248-MS
... algorithms based on machine learning techniques. Hence, it can therefore be inferred that machine learning approach has the ability to predict reservoir parameters. neural network presented artificial intelligence reservoir characterization machine learning upstream oil & gas porosity deep...
Proceedings Papers

Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 2–4, 2021
Paper Number: SPE-208246-MS
... neural network well intervention gas production principal component production enhancement information production monitoring downhole intervention upstream oil & gas oil production immediate attention identify potential candidate well identification international petroleum technology...
Proceedings Papers

Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 2–4, 2021
Paper Number: SPE-208249-MS
... with python has the ability to visualize, model and analyze wells performances. This technique will petroleum engineers to better monitor evaluate and enhance their production operation without the need for expensive softwares. This will reduce operating cost increases revenue. neural network nigeria...
Proceedings Papers

Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 2–4, 2021
Paper Number: SPE-208242-MS
... contribution to promoting a healthy and safe oil and gas work environment. personnel competence neural network artificial intelligence immunology affability health & medicine oil and gas sector mental state upstream oil & gas ei quotient covid-19 gas worker nigeria oil & gas...
Proceedings Papers

Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 2–4, 2021
Paper Number: SPE-208259-MS
... (AI) for securing Nigeria’s pipeline network. The review focuses on summarizing available evidence on the use of some relevant AI components such as Image Analytics, Convolutional Neural Network (CNN) as well as Edge-Based AI Solutions, for securing oil pipelines. Based on the findings of case studies...
Proceedings Papers

Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 2–4, 2021
Paper Number: SPE-208450-MS
... on learning from past events. machine learning drilling operation optimization problem engineering accuracy rop neural network non-linear relationship prediction autonomous rotary drilling system exhibition application penetration rate artificial intelligence upstream oil & gas input...
Proceedings Papers

Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 2–4, 2021
Paper Number: SPE-208452-MS
.... The first attempt at modelling the Surfactant-Polymer (SP) EOR process with ML was executed by Karambeigi et al. [ 28 ] where Multi-Layer Perceptron (MLP) Neural Network was developed for predicting the RF and NPV of the process. Half-normal probability plots from statistical DoE were used for sensitivity...

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