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Related papers: Mind the Gap: A Well Log Data Analysis

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Drilling boreholes for gas and oil extraction is an expensive process and profitability strongly depends on characteristics of the subsurface. As profitability is a key success factor, companies in the industry utilise well logs to explore…

Machine Learning · Computer Science 2020-10-12 Vito Alexander Nordloh , Anna Roubícková , Nick Brown

The objective is to study the feasibility of predicting subsurface rock properties in wells from real-time drilling data. Geophysical logs, namely, density, porosity and sonic logs are of paramount importance for subsurface resource…

Geophysics · Physics 2020-09-09 Rayan Kanfar , Obai Shaikh , Mehrdad Yousefzadeh , Tapan Mukerji

The gamma-ray logging method is one of the mandatory well logging methods for geophysical exploration of wells. However, during the conduct of such a study, the sensor, for one reason or another, may stop recording observations in the well.…

Applications · Statistics 2018-07-04 N. S. Churikov , N. G. Grafeeva

One of the first steps during the investigation of geological objects is the interwell correlation. It provides information on the structure of the objects under study, as it comprises the framework for constructing geological models and…

Obtaining reliable permeability maps of oil reservoirs is crucial for building a robust and accurate reservoir simulation model and, therefore, designing effective recovery strategies. This problem, however, remains challenging, as it…

The process of exploring and exploiting Oil and Gas (O&G) generates a lot of data that can bring more efficiency to the industry. The opportunities for using data mining techniques in the "digital oil-field" remain largely unexplored or…

Artificial Intelligence · Computer Science 2017-05-29 Alipio Jorge , German Larrazabal , Pablo Guillen , Rui L. Lopes

Millions of abandoned oil and gas wells are scattered across the world, leaching methane into the atmosphere and toxic compounds into the groundwater. Many of these locations are unknown, preventing the wells from being plugged and their…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Pratinav Seth , Michelle Lin , Brefo Dwamena Yaw , Jade Boutot , Mary Kang , David Rolnick

Non-core drilling has gradually become the primary exploration method in geological exploration engineering, and well logging curves have increasingly gained importance as the main carriers of geological information. However, factors such…

Machine Learning · Computer Science 2024-01-04 Yuankai Zhou , Huanyu Li

The rise in energy demand highlights the importance of suitable subsurface storage, requiring detailed and accurate subsurface characterization often reliant on high-quality borehole well log data. However, obtaining complete well-log data…

Drilling activities in the oil and gas industry have been reported over decades for thousands of wells on a daily basis, yet the analysis of this text at large-scale for information retrieval, sequence mining, and pattern analysis is very…

Computation and Language · Computer Science 2017-12-06 Júlio Hoffimann , Youli Mao , Avinash Wesley , Aimee Taylor

Modern geosciences have to deal with large quantities and a wide variety of data, including 2-D, 3-D and 4-D seismic surveys, well logs generated by sensors, detailed lithological records, satellite images and meteorological records. These…

Geophysics · Physics 2018-09-12 Youzuo Lin , Weichang Li , Alipio Jorge , Rui L. Lopes , German Larrazabal , Pablo Guillen

Early detection of energy losses, theft, and operational inefficiencies remains a critical challenge in oil and gas production systems due to complex interdependencies among wells and facilities, evolving operating conditions, and limited…

Machine Learning · Computer Science 2026-03-17 AbdulQoyum A. Olowookere , Adewale U. Oguntola , Ebenezer. Leke Odekanle

Manual interpretation of data collected from drill holes for mineral or oil and gas exploration is time-consuming and subjective. Identification of geological boundaries and distinctive rock physical property domains is the first step of…

Geophysics · Physics 2020-02-19 Ayham Zaitouny , Michael Small , June Hill , Irina Emelyanova , M. Ben Clennell

Enhanced lithological interpretation from well logs plays a key role in geological resource exploration and mapping, as well as in geo-environmental modeling studies. Core and cutting information is useful for making sound interpretations…

Geophysics · Physics 2025-12-16 Raj Sahu , Saumen Maiti

This paper proposes a complete framework consisting pre-processing, modeling, and post-processing stages to carry out well tops guided prediction of a reservoir property (sand fraction) from three seismic attributes (seismic impedance,…

Neural and Evolutionary Computing · Computer Science 2015-10-06 Soumi Chaki , Akhilesh K Verma , Aurobinda Routray , William K Mohanty , Mamata Jenamani

Low oil prices have motivated energy executives to look into cost reduction in their supply chains more seriously. To this end, a new technology that is experimentally considered in hydrocarbon exploration is data mining. There are two…

Other Computer Science · Computer Science 2017-05-19 Hamed Nikhalat Jahromi , Alpio M. Jorge

Logs are valuable information for oil and gas fields as they help to determine the lithology of the formations surrounding the borehole and the location and reserves of subsurface oil and gas reservoirs. However, important logs are often…

Machine Learning · Computer Science 2023-08-25 Hua Wang , Yuqiong Wu , Yushun Zhang , Fuqiang Lai , Zhou Feng , Bing Xie , Ailin Zhao

Geoscience domain experts traditionally correlate formation tops in the subsurface using geophysical well logs (known as well-log correlation) by-hand. Based on individual well log interpretation and well-to-well comparisons, these…

Information Retrieval · Computer Science 2022-02-21 Jesse R. Pisel , Joshua A. Dierker , Sanya Srivastava , Samira B. Ravilisetty , Michael J. Pyrcz

This field case study aims to address the challenge of accurately predicting petrophysical properties in heterogeneous reservoir formations, which can significantly impact reservoir performance predictions. The study employed three machine…

Geophysics · Physics 2023-05-15 Fethi Ali Cheddad

We present a data-driven and physics-informed algorithm for drilling accident forecasting. The core machine-learning algorithm uses the data from the drilling telemetry representing the time-series. We have developed a Bag-of-features…

Machine Learning · Computer Science 2022-03-11 Ekaterina Gurina , Nikita Klyuchnikov , Ksenia Antipova , Dmitry Koroteev
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