Article

Otchere, D.A. and Latiff, A.H. and Tackie-Otoo, B.N. (2024) Distributed acoustic sensing in subsurface applications � Review and potential integration with artificial intelligence for an intelligent CO2 storage monitoring system. Geoenergy Science and Engineering, 237.

Tackie-Otoo, B.N. and Otchere, D.A. and Latiff, A.H.A. and Ayoub Mohammed, M.A. and Hassan, A.M. (2024) Evaluation of the Oil Recovery Potential and Cost Implication Analysis of Alternative ASP Formulations for Sandstone and Carbonate Reservoirs. ACS Omega, 9 (19). pp. 20859-20875.

Otchere, D.A. (2024) Fundamental error in tree-based machine learning model selection for reservoir characterisation. Energy Geoscience, 5 (2).

Tabaaza, G.A. and Tackie-Otoo, B.N. and Zaini, D.B. and Otchere, D.A. and Lal, B. (2023) Application of machine learning models to predict cytotoxicity of ionic liquids using VolSurf principal properties. Computational Toxicology, 26.

Lawal, M. and Hassan, M.H.A. and Abdullah, W.H. and Otchere, D.A. (2023) Sedimentary facies and stratigraphy of the Campanian-Maastrichtian Taloka Formation, southeastern Iullemmeden Basin, Nigeria. Journal of African Earth Sciences, 200.

Tackie-Otoo, B.N. and Ayoub Mohammed, M.A. and Otchere, D.A. and Jufar, S.R. (2023) A study of the oil recovery potential and mechanisms of an alternative Alkaline-Surfactant-Polymer formulation for carbonate reservoir. Geoenergy Science and Engineering, 227.

Otchere, D.A. and Ganat, T.O.A. and Ojero, J.O. and Tackie-Otoo, B.N. and Taki, M.Y. (2022) Application of gradient boosting regression model for the evaluation of feature selection techniques in improving reservoir characterisation predictions. Journal of Petroleum Science and Engineering, 208. ISSN 09204105

Otchere, D.A. and Ganat, T.A.O. and Gholami, R. (2022) Contact angle measurements: a critical review of laboratory parametric effect and prospect. International Journal of Oil, Gas and Coal Technology, 31 (1). pp. 51-78. ISSN 17533309

Otchere, D.A. and Ganat, T.O.A. and Nta, V. and Brantson, E.T. and Sharma, T. (2022) Data analytics and Bayesian Optimised Extreme Gradient Boosting approach to estimate cut-offs from wireline logs for net reservoir and pay classification. Applied Soft Computing, 120. ISSN 15684946

Otchere, D.A. and Tackie-Otoo, B.N. and Mohammad, M.A.A. and Ganat, T.O.A. and Kuvakin, N. and Miftakhov, R. and Efremov, I. and Bazanov, A. (2022) Improving seismic fault mapping through data conditioning using a pre-trained deep convolutional neural network: A case study on Groningen field. Journal of Petroleum Science and Engineering, 213. ISSN 09204105

Otchere, D.A. and Mohammed, M.A.A. and Ganat, T.O.A. and Gholami, R. and Merican, Z.M.A. (2022) A Novel Empirical and Deep Ensemble Super Learning Approach in Predicting Reservoir Wettability via Well Logs. Applied Sciences (Switzerland), 12 (6). ISSN 20763417

Otchere, D.A. and Arbi Ganat, T.O. and Gholami, R. and Ridha, S. (2021) Application of supervised machine learning paradigms in the prediction of petroleum reservoir properties: Comparative analysis of ANN and SVM models. Journal of Petroleum Science and Engineering, 200. ISSN 09204105

Tackie-Otoo, B.N. and Atta, D.Y. and Ayoub Mohammed, M.A. and Otchere, D.A. (2021) Investigation into the Oil Recovery Process Using an Organic Alkali-Amino Acid-Based Surfactant System. Energy and Fuels, 35 (14). pp. 11171-11192. ISSN 08870624

Otchere, D.A. and Ganat, T.O.A. and Gholami, R. and Lawal, M. (2021) A novel custom ensemble learning model for an improved reservoir permeability and water saturation prediction. Journal of Natural Gas Science and Engineering, 91. ISSN 18755100

Conference or Workshop Item

Otchere, D.A. and Latiff, A.H.A. and Taki, M.Y. and Dafyak, L.A. (2023) Machine-Learning-Based Proxy Modelling for Geothermal Field Development Optimisation. In: UNSPECIFIED.

Rashid, A. and Siddiqui, N.A. and Ahmed, N. and Jamil, M. and Otchere, D.A. and Kasim, S.A. (2022) Field Characteristics of Sedimentary Rocks in the Dohol Formation, Johor, Peninsular Malaysia. In: UNSPECIFIED.

Otchere, D.A. and Hodgetts, D. and Ganat, T.A.O. and Ullah, N. and Rashid, A. (2021) Static Reservoir Modeling Comparing Inverse Distance Weighting to Kriging Interpolation Algorithm in Volumetric Estimation. Case Study: Gullfaks Field. In: UNSPECIFIED.

Book

Otchere, D.A. (2024) Application of a Novel Stacked Ensemble Model in Predicting Total Porosity and Free Fluid Index via Wireline and NMR Logs. CRC Press, pp. 33-56. ISBN 9781003860198; 9781032433646

Brantson, E.T. and Iyiola, Z.O. and Ziggah, Y.Y. and Mensah, A.O. and Otchere, D.A. and Abakah-Paintsil, E.E. and Duodu, E.K. (2024) Carbon Dioxide Low Salinity Water Alternating Gas (CO2 LSWAG) Oil Recovery Factor Prediction in Carbonate Reservoir Using Supervised Machine Learning Models. CRC Press, pp. 125-158. ISBN 9781003860198; 9781032433646

Otchere, D.A. and Gholami, R. and Nta, V. and Ganat, T.O.A. (2024) Compressional and Shear Sonic Log Determination Using Data-Driven Machine Learning Techniques. CRC Press, pp. 57-86. ISBN 9781003860198; 9781032433646

Otchere, D.A. and Mohammed, M.A.A. (2024) Data-driven and Machine Learning Approach in Estimating Multi-zonal ICV Water Injection Rates in a Smart Well Completion. CRC Press, pp. 104-124. ISBN 9781003860198; 9781032433646

Otchere, D.A. and Mohammed, M.A.A. and Al-Hadrami, H. and Boakye, T.B. (2024) Enhancing Drilling Fluid Lost-circulation Prediction: Using Model Agnostic and Supervised Machine Learning. CRC Press, pp. 6-32. ISBN 9781003860198; 9781032433646

Otchere, D.A. and Latiff, A.H. and Kuvakin, N. and Miftakhov, R. and Efremov, I. and Bazanov, A. (2024) Improving Seismic Salt Mapping through Transfer Learning Using A Pre-trained Deep Convolutional Neural Network A Case Study on Groningen Field. CRC Press, pp. 159-180. ISBN 9781003860198; 9781032433646

Otchere, D.A. and Latiff, A.H. and Kuvakin, N. and Miftakhov, R. and Efremov, I. and Bazanov, A. (2024) Super-Vertical-Resolution Reconstruction of Seismic Volume Using A Pre-trained Deep Convolutional Neural Network A Case Study on Opunake Field. CRC Press, pp. 181-206. ISBN 9781003860198; 9781032433646