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Keywords: machine learning
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Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 10–12, 2023
Paper Number: SPE-215409-MS
..., water and gas injection facilities were installed, and these secondary recovery floods operated on selected reservoir intervals with reasonable degree of success. Background upstream oil & gas artificial intelligence operation united states government machine learning breakthrough...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 10–12, 2023
Paper Number: SPE-215449-MS
... Figure 3 NMR T2 fluid substitution for HI correction NMR T<sub>2</sub> Clustering using Machine Learning (ML) Factor Analysis Once we have obtained the 100% water response of the T 2 distribution (T2DIST_100W_FSUB), which reveals the actual rock properties and pore size...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 10–12, 2023
Paper Number: SPE-215236-MS
... waterflood management solution combines cloud technologies, big data processing, data analytics, machine learning algorithms, robotics, sensors and monitoring system, automation, edge gateways, and augmented and virtual reality (AR/VR). Design thinking principles and a human-centric approach within an agile...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 10–12, 2023
Paper Number: SPE-215253-MS
... the joint distribution of high dimensional image data. The results show that the Co-GAN surrogate model can accurately predict reservoir pressure and fluid saturation, and thus can accurately predict oil well production. So far, machine learning models based on partial differential equations...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 10–12, 2023
Paper Number: SPE-215222-MS
... to human error and human bias. To maximize the utilization of unstructured data, a machine learning (ML) based solution is proposed to develop new sand control best practices to enhance oil and gas production in new and mature fields. The ‘ multi-modal’ solution utilizes ML technology stack such as Deep...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 10–12, 2023
Paper Number: SPE-215260-MS
... Abstract The objective of this study is to predict EOR efficiencies through static wettability contact angle measurement by Machine Learning (ML) modeling. Unlike conventional methods of measuring static wettability contact angle, the unconventional digital static wettability contact angle...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 10–12, 2023
Paper Number: SPE-215205-MS
... Abstract Advances in machine learning algorithm and the discoveries of various open source codes in recent years have led to a new insight in utilizing legacy data to delve into the unknown generating something out of poor data availability and presence. Subsurface evaluation of reservoir...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 10–12, 2023
Paper Number: SPE-215327-MS
... machine learning sedimentary geothermal reservoir workflow intelligent detection quartz segmentation geothermal sedimentary reservoir The prevalent method for analyzing quartz overgrowth in these reservoirs involves the use of Scanning Electron Microscopy (SEM) images. In the case of quartz...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 10–12, 2023
Paper Number: SPE-215292-MS
... of hydraulic fracturing and fluid flow, provides detailed understanding ( Weng et al., 2011 ; Singh et al, 2020 ). However, its high cost and technical complexity render it less practical for daily use in unconventional plays ( Tan et al., 2018 ). Abstract Several studies have used machine learning...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 10–12, 2023
Paper Number: SPE-215274-MS
... learning production oil 15 breakthrough injection polymer injection utilizing petroleum science katterbauer water 15 deep learning log interpretation framework norway government water management machine learning carbon footprint residual polymer efficiency Introduction Field...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 10–12, 2023
Paper Number: SPE-215265-MS
... conducted, and the results were stored in a database within a data lake. Multiple machine learning algorithms were evaluated to determine the most suitable algorithm for deployment. Python programming is subsequently initiated and deployed within the cloud service environment, and the results...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 10–12, 2023
Paper Number: SPE-215326-MS
... a flow-after-flow test may be generated without ever performing the actual test. A machine learning (ML) model developed and trained on historic production data is used to simulate a producing wells performance at several rates as is typical for an actual flow-after-flow test. The methodology utilizes...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 10–12, 2023
Paper Number: SPE-215318-MS
... production control petroleum engineer surveillance production monitoring value liquified natural gas (lng) reservoir surveillance calculation society mrt reservoir surveillance data node reliability field producing machine learning information voi calculation paper Introduction...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 10–12, 2023
Paper Number: SPE-215306-MS
... development upstream oil &amp; gas reservoir simulation production control reservoir characterization co 2 scaling method climate change equation of state europe government enhanced recovery cgnet machine learning sequestration partition aquifer saturation calibrate brine extraction...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 10–12, 2023
Paper Number: SPE-215341-MS
... testing asia government united states government upstream oil &amp; gas neural network drillstem testing production logging production control artificial intelligence machine learning deep learning production forecasting reservoir surveillance equation history matching reservoir simulation...
Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 10–12, 2023
Paper Number: SPE-215380-MS
...Machine Learning Algorithm for Predicting Maximum Hole Diameter This paper describes a machine learning algorithm that is used to predict mechanical caliper log using LWD data. Available LWD data from different wells were used to build the algorithm in Python. The algorithm is first trained...

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