Results 1 to 10 of about 80,361 (310)

New Empirical Models for Estimating Permeability in One of Southern Iranian Carbonate Fields using NMR-Derived Features [PDF]

Journal of Chemical and Petroleum Engineering, 2020
Permeability is arguably the most important property in evaluating fluid flow in the reservoir. It is also one of the most difficult parameters to measure in field.
Shahin Parchekhari, Ali Nakhaee, Ali Kadkhodaie   +2 more
doaj   +1 more source

Application of Log Lithofacies Classification Model Based on Clustering-Support Vector Classification Method

Cejing jishu, 2023
The carbonate reservoir in study area A of the Middle East has good reservoir quality. However, in this area, the pore types are numerous, the pore structure is complex, and the heterogeneity difference between wells is really strong.
HE Xianhong, LI Kesai, XU Jiacheng, FU Meiyan, YANG Yufei, SUN Jiaqi   +5 more
doaj   +1 more source

Source rock geochemical assessment and estimation of TOC using well logs and geochemical data of Talhar Shale, Southern Indus Basin, Pakistan

Frontiers in Earth Science, 2022
Assessment of organic carbon content (TOC) by geophysical logs has been a challenging task in the formation evaluation of shale gas. This research is conducted to estimate the unconventional hydrocarbon (shale-gas) potential of Talhar Shale in the ...
Humayun Khalil Khan, Muhsan Ehsan, Abid Ali, Muhammad Attique Amer, Haroon Aziz, Abdullah Khan, Yasir Bashir, Tamer Abu-Alam, Mohamed Abioui   +8 more
doaj   +1 more source

Research on prediction methods of formation pore pressure based on machine learning

Energy Science & Engineering, 2022
Formation pressure is the most fundamental data in oil and gas drilling and production; it has an important position in the entire cycle of oil and gas extraction.
Honglin Huang, Jun Li, Hongwei Yang, Biao Wang, Reyu Gao, Ming Luo, Wentuo Li, Geng Zhang, Liu Liu   +8 more
doaj   +1 more source

A Seq2Seq Model Improved by Transcendental Learning and Imaged Sequence Samples for Porosity Prediction

Mathematics, 2022
Since the accurate prediction of porosity is one of the critical factors for estimating oil and gas reservoirs, a novel porosity prediction method based on Imaged Sequence Samples (ISS) and a Sequence to Sequence (Seq2Seq) model fused by Transcendental ...
Lijian Zhou, Lijun Wang, Zhiang Zhao, Yuwei Liu, Xiwu Liu   +4 more
doaj   +1 more source

Classification of Void Space Types in Fractured-Vuggy Carbonate Reservoir Using Geophysical Logging: A Case Study on the Sinian Dengying Formation of the Sichuan Basin, Southwest China

Energies, 2021
The fractured-vuggy carbonate reservoirs display strong heterogeneity and need to be classified into different types for specific characterization. In this study, a total of 134 cores from six drilled wells and six outcrops of the Deng #2 and Deng #4 ...
Kunyu Wang, Juan Teng, Hucheng Deng, Meiyan Fu, Hongjiang Lu   +4 more
doaj   +1 more source

Adaptive log compression for massive log data [PDF]

Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, 2013
We present a novel adaptive log compression scheme. Results show 30% improvement on compression ratios over existing approaches.
Robert Christensen, Feifei Li 0001
openaire   +1 more source

Prediction model of TOC contents in source rocks with different salinity degrees based on Support Vector Machine (SVM)

Shiyou shiyan dizhi, 2022
The total organic carbon (TOC) content is an important parameter for the evaluation of abundance of organic matter in source rocks, and its predicting accuracy is of great significance to oil and gas exploration and development.
Yongzhi CHU, Chenglin LIU, Wanxue TAI, Hong YANG   +3 more
doaj   +1 more source

A Taxonomy of Anomalies in Log Data

, 2022
Log data anomaly detection is a core component in the area of artificial intelligence for IT operations. However, the large amount of existing methods makes it hard to choose the right approach for a specific system. A better understanding of different kinds of anomalies, and which algorithms are suitable for detecting them, would support researchers ...
Thorsten Wittkopp, Philipp Wiesner, Dominik Scheinert, Odej Kao   +3 more
openaire   +2 more sources

Logging Data Completion Based on an MC-GAN-BiLSTM Model

IEEE Access, 2022
Due to environmental interference and operational errors, problems such as incomplete and random missing logging data have occurred during the geophysical logging data collection process.
Liang Guo, Luo Renze, Li Xingyu, Tuo Juanjuan, Canru Lei, Zhou Yang   +5 more
doaj   +1 more source