Open Hole-Wireline Logging to Determine the Characteristics of the Reservoir

Mohamed Imdath A; Mohammed Usama M.B; Rifan M; Sheik Abdulla M; A. Nagarajan; K. Bogeswaran

Mohamed Imdath A Department of Petroleum Engineering, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India
Mohammed Usama M.B Department of Petroleum Engineering, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India
Rifan M Department of Petroleum Engineering, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India.
Sheik Abdulla M Department of Petroleum Engineering, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India
A. Nagarajan Assistant Professor, Department of Petroleum Engineering, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India.
K. Bogeswaran Assistant Professor, Department of Petroleum Engineering, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India.

Keywords: Open hole, Wireline logging, Porosity, Permeability, Shale volume, logging tools, Resistivity logs, Lithology, logs, Water saturation, Parameters.

Abstract

Openhole well logging encompasses a diverse range of measurements, including as measurement-while-drilling (MWD) logs, standard wireline logs, and mud logs. These measurements are the major source of formation evaluation data, and they are used in applications ranging from individual drilling-well appraisals to extensive reservoir description studies. They are also known as "logs." The technology for openhole well-logging is continuously being developed in response to the demand for increased precision in determining the features of reservoirs. Recent years have seen a proliferation of various technical advancements. This article offers a number of recent innovations and applications to demonstrate the current state of technology and to offer insight into the patterns that will guide its future growth.

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118. Sahoo, A. K., & Samal, S. K. (2023). Online fault detection and classification of 3-phase long transmission line using machine learning model. Multiscale and Multidisciplinary Modeling, Experiments and Design, 6(1), 135-146.
119. A. Patel, S. Samal, S. Ghosh and B. Subudhi, "A study on wide-area controller design for inter-area oscillation damping," 2016 2nd International Conference on Control, Instrumentation, Energy & Communication (CIEC), Kolkata, India, 2016, pp. 245-249.
120. Meng, F., Jagadeesan, L., & Thottan, M. (2021). Model-based reinforcement learning for service mesh fault resiliency in a web application-level. arXiv preprint arXiv:2110.13621.
121. Meng, F., Zhang, L., & Chen, Y. (2023) FEDEMB: An Efficient Vertical and Hybrid Federated Learning Algorithm Using Partial Network Embedding.
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124. Awais, M., Bhuva, A., Bhuva, D., Fatima, S., & Sadiq, T. (2023). Optimized DEC: An effective cough detection framework using optimal weighted Features-aided deep Ensemble classifier for COVID-19. Biomedical Signal Processing and Control, 105026.
125. D. R. Bhuva and S. Kumar, “A novel continuous authentication method using biometrics for IOT devices,” Internet of Things, vol. 24, p. 100927, 2023.
126. D. Bhuva and S. Kumar, "Securing Space Cognitive Communication with Blockchain," 2023 IEEE Cognitive Communications for Aerospace Applications Workshop (CCAAW), Cleveland, OH, USA, 2023, pp. 1-6.
127. D. S. Das, D. Gangodkar, R. Singh, P. Vijay, A. Bhardwaj and A. Semwal, "Comparative Analysis of Skin Cancer Prediction using Neural Networks and Transfer Learning," 2022 5th International Conference on Contemporary Computing and Informatics (IC3I), Uttar Pradesh, India, 2022, pp. 367-371.
128. A. Bhardwaj, J. Pattnayak, D. Prasad Gangodkar, A. Rana, N. Shilpa and P. Tiwari, "An Integration of Wireless Communications and Artificial Intelligence for Autonomous Vehicles for the Successful Communication to Achieve the Destination," 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), Greater Noida, India, 2023, pp. 748-752.
129. A. Bhardwaj, S. Rebelli, A. Gehlot, K. Pant, J. L. A. Gonzáles and F. A., "Machine learning integration in Communication system for efficient selection of signals," 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), Greater Noida, India, 2023, pp. 1529-1533.
130. A. Bhardwaj, R. Raman, J. Singh, K. Pant, N. Yamsani and R. Yadav, "Deep Learning-Based MIMO and NOMA Energy Conservation and Sum Data Rate Management System," 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), Greater Noida, India, 2023, pp. 866-871.
131. V. Bansal, A. Bhardwaj, J. Singh, D. Verma, M. Tiwari and S. Siddi, "Using Artificial Intelligence to Integrate Machine Learning, Fuzzy Logic, and The IOT as A Cybersecurity System," 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), Greater Noida, India, 2023, pp. 762-769.
132. A. Chaturvedi, A. Bhardwaj, D. Singh, B. Pant, J. L. A. Gonzáles and F. A., "Integration of DL on Multi-Carrier Non-Orthogonal Multiple Access System with Simultaneous Wireless Information and Power Transfer," 2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART), Moradabad, India, 2022, pp. 640-643.
133. A. Uthiramoorthy, A. Bhardwaj, J. Singh, K. Pant, M. Tiwari and J. L. A. Gonzáles, "A Comprehensive review on Data Mining Techniques in managing the Medical Data cloud and its security constraints with the maintained of the communication networks," 2023 International Conference on Artificial Intelligence and Smart Communication (AISC), Greater Noida, India, 2023, pp. 618-623.
134. D. K. Sharma, B. Singh, R. Regin, R. Steffi, and M. K. Chakravarthi, “Efficient Classification for Neural Machines Interpretations based on Mathematical models,” in 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), 2021.
135. F. Arslan, B. Singh, D. K. Sharma, R. Regin, R. Steffi, and S. Suman Rajest, “Optimization technique approach to resolve food sustainability problems,” in 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), 2021.
136. G. A. Ogunmola, B. Singh, D. K. Sharma, R. Regin, S. S. Rajest, and N. Singh, “Involvement of distance measure in assessing and resolving efficiency environmental obstacles,” in 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), 2021.
137. D. K. Sharma, B. Singh, M. Raja, R. Regin, and S. S. Rajest, “An Efficient Python Approach for Simulation of Poisson Distribution,” in 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), 2021.
138. K. Sharma, B. Singh, E. Herman, R. Regine, S. S. Rajest, and V. P. Mishra, “Maximum information measure policies in reinforcement learning with deep energy-based model,” in 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), 2021.
139. D. K. Sharma, N. A. Jalil, R. Regin, S. S. Rajest, R. K. Tummala, and Thangadurai, “Predicting network congestion with machine learning,” in 2021 2nd International Conference on Smart Electronics and Communication (ICOSEC), 2021
140. Chakrabarti P. ,Chakrabarti T., Sharma M . , Atre D, Pai K.B., “Quantification of Thought Analysis of Alcohol-addicted persons and memory loss of patients suffering from stage-4 liver cancer”, Advances in Intelligent Systems and Computing, 1053, pp.1099-1105, 2020.
141. Chakrabarti P., Bane S.,Satpathy B.,Goh M, Datta B N , Chakrabarti T., “Compound Poisson Process and its Applications in Business”, Lecture Notes in Electrical Engineering, 601, pp.678-685,2020.
142. Chakrabarti P., Chakrabarti T., Satpathy B., SenGupta I . Ware J A., “Analysis of strategic market management in the light of stochastic processes, recurrence relation, Abelian group and expectation”, Advances in Artificial Intelligence and Data Engineering, 1133 , pp.701-710, 2020.
143. Priyadarshi N., Bhoi A.K., Sharma A.K., Mallick P.K. , Chakrabarti P., “An efficient fuzzy logic control-based soft computing technique for grid-tied photovoltaic system”, Advances in Intelligent Systems and Computing, 1040,pp.131-140,2020.
144. Priyadarshi N., Bhoi A.K., Sahana S.K., Mallick P.K. , Chakrabarti P., Performance enhancement using novel soft computing AFLC approach for PV power system”, Advances in Intelligent Systems and Computing, 1040, pp.439-448,2020.
145. Magare A., Lamin M., Chakrabarti P., “Inherent Mapping Analysis of Agile Development Methodology through Design Thinking”, Lecture Notes on Data Engineering and Communications Engineering, 52, pp.527-534,2020.
146. Ali Y., Shreemali J., Chakrabarti T., Chakrabarti P. , Poddar S., “Prediction of Reaction Parameters on Reaction Kinetics for Treatment of Industrial Wastewater: A Machine Learning Perspective”, Materials Today :Proceedings,2020.
147. Chakrabarti P., Satpathy B., Bane S., Chakrabarti T., Poddar S., “Business gain forecasting in Materials Industry - A linear dependency, exponential growth, moving average, neuro-associator and compound Poisson process perspective”, Materials Today: Proceedings, 2020.