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Keywords: machine learning
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Journal Articles
Petrophysics 63 (05): 591–603.
Paper Number: SPWLA-2022-v63n5a2
Published: 01 October 2022
... shale oil machine learning wetting-phase saturation doi variation regression coefficient relation genuchten engineering university capillary pressure empirical relation formation colorado conduit PETROPHYSICS, VOL. 63, NO. 5 (OCTOBER 2022); PAGES 591 603; 10 FIGURES, 3 TABLES. DOI...
Journal Articles
Petrophysics 63 (04): 506–518.
Paper Number: SPWLA-2022-v63n4a2
Published: 02 August 2022
... workflow doi log analysis machine learning resistivity measurement plane geophysics well logging reservoir characterization drilling measurement inversion module boundary lwd resistivity measurement real-time 2 geosteering application university PETROPHYSICS, VOL. 63, NO. 4 (AUGUST 2022...
Journal Articles
Petrophysics 63 (04): 534–548.
Paper Number: SPWLA-2022-v63n4a4
Published: 02 August 2022
... 3 2022 2 8 2022 2 8 2022 Copyright 2022, Society of Petrophysicists & Well Log Analysts artificial intelligence realization bayesian inference machine learning porosity log analysis database upstream oil & gas well logging probability reservoir...
Journal Articles
Petrophysics 63 (04): 549–565.
Paper Number: SPWLA-2022-v63n4a5
Published: 02 August 2022
... 2022, Society of Petrophysicists & Well Log Analysts upstream oil & gas structural geology log analysis facies well logging artificial intelligence machine learning pearl river mouth basin resistivity fracture reservoir characterization porosity interpretation den doi...
Journal Articles
Petrophysics 63 (03): 277–289.
Paper Number: SPWLA-2022-v63n3a1
Published: 01 June 2022
... artificial intelligence immobile hydrocarbon conocophillips contact angle integrated reservoir characterization hydrocarbon workflow petrophysics june 2022 machine learning well logging water saturation nmr unsupervised learning june 2022 signature nuclear magnetic resonance university...
Journal Articles
Petrophysics 63 (03): 442–453.
Paper Number: SPWLA-2022-v63n3a10
Published: 01 June 2022
... data should be better explored to improve the accuracy of permeability estimates. 29 9 2021 10 12 2021 13 12 2021 1 6 2022 1 6 2022 Copyright 2022, Society of Petrophysicists & Well Log Analysts core analysis machine learning artificial intelligence enhanced...
Journal Articles
Petrophysics 63 (03): 290–299.
Paper Number: SPWLA-2022-v63n3a2
Published: 01 June 2022
...Steve Cuddy This paper describes the application of machine-learning techniques for unlocking the full potential of nuclear magnetic resonance (NMR), using a case study from the Seven Heads gas field. This field has long been recognized but was not developed due to a variety of technical challenges...
Journal Articles
Petrophysics 63 (03): 300–338.
Paper Number: SPWLA-2022-v63n3a3
Published: 01 June 2022
..., 2012). Hence, care should be taken when applying these methods to NMR laboratory data. A few latest NMR data processing trends or important topics are not covered in detail in this paper. One of them is to apply machine learning and data analysis to NMR interpretation. For example, Anand et al. (2017a...
Journal Articles
Petrophysics 63 (03): 352–367.
Paper Number: SPWLA-2022-v63n3a5
Published: 01 June 2022
... and permeability assessment than typical T 2 - or T 1 -cutoff methods. Copyright 2022, Society of Petrophysicists & Well Log Analysts 24 9 2021 28 10 2021 29 10 2021 1 6 2022 1 6 2022 reservoir characterization artificial intelligence log analysis shale gas machine...
Journal Articles
Journal Articles
Petrophysics 63 (02): 218–236.
Paper Number: SPWLA-2022-v63n2-a5
Published: 01 April 2022
... 2022 Copyright 2022, Society of Petrophysicists & Well Log Analysts machine learning drilling fluids and materials base oil content solubility drilling fluid selection and formulation fluid loss control variation mpa drilling fluid chemistry drilling fluid property upstream...
Journal Articles
Petrophysics 63 (01): 12–34.
Paper Number: SPWLA-2022-v63n1a2
Published: 01 February 2022
... & Well Log Analysts machine learning artificial intelligence reservoir characterization neural network log analysis deep learning february 2022 euclidean distance correlation well 16 pearson correlation petrophysics february 2022 well logging upstream oil & gas automated well-log...
Journal Articles
Petrophysics 63 (01): 35–60.
Paper Number: SPWLA-2022-v63n1a3
Published: 01 February 2022
... practices and implementations using machine learning (ML) and automation. This will enable geoscientists to explore and exploit vast amounts of data quickly and efficiently. To address these current industry challenges, we propose a pilot well-log database in HDF5 (Hierarchical Data Format version 5) format...
Journal Articles
Petrophysics 62 (06): 585–613.
Paper Number: SPWLA-2021-v62n6a1
Published: 01 December 2021
... data. Having vast quantities of data does not mean it can all be passed into a machine-learning algorithm with the expectation that the resultant prediction is fit for purpose. It is essential that the most important and relevant data are passed into the model through appropriate feature selection...
Journal Articles
Petrophysics 62 (06): 614–629.
Paper Number: SPWLA-2021-v62n6a2
Published: 01 December 2021
...Paul R. Craddock; Prakhar Srivastava; Harish Datir; David Rose; Tong Zhou; Laurent Mosse; Lalitha Venkataramanan This paper describes an innovative machine-learning application, based on variational autoencoder frameworks, to quantify the concentrations and associated uncertainties of common...
Journal Articles
Petrophysics 62 (06): 636–650.
Paper Number: SPWLA-2021-v62n6a4
Published: 01 December 2021
..., and versions, such as VGGnet (Simonyan and Zisserman, 2015) then passing through a machine-learning method to carry out and GoogLeNet (Szegedy et al., 2015), achieved even the classification task. better performance in classification. A big step forward for CNN performance in image classification was achieved...
Journal Articles
Journal Articles
Petrophysics 62 (04): 353–361.
Paper Number: SPWLA-2021-v62n4a1
Published: 01 August 2021
... Log Analysts well logging criterion reinforcement learning neural network machine learning artificial intelligence multiple well-log depth matching log analysis upstream oil & gas experiment houston agent q-value optimal action university deep q-network algorithm reference...
Journal Articles
Petrophysics 62 (04): 393–406.
Paper Number: SPWLA-2021-v62n4a4
Published: 01 August 2021
... on multivariate regression or rock physics relations. Started on March 1, 2020, and concluded on May 7, 2020, the SPWLA PDDA SIG hosted a contest aiming to predict the DTC and DTS logs from seven “easy-to-acquire” conventional logs using machine-learning methods (GitHub, 2020). In the contest, a total number...
Journal Articles
Petrophysics 62 (04): 407–421.
Paper Number: SPWLA-2021-v62n4a5
Published: 01 August 2021
... imager (HROBMI) tool. This new multifrequency imaging tool is able to function at high frequencies (in the MHz range) in oil-based muds. To allow for the quantitative estimation of formation and mud properties from the HROBMI data, a hybrid machine-learning/inversion approach was implemented...

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