FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4297521545> ?p ?o ?g. }

• W4297521545 endingPage "7126" @default.
• W4297521545 startingPage "7126" @default.
• W4297521545 abstract "The carboniferous carbonate reservoirs in the North Truva Oilfield have undergone complex sedimentation, diagenesis and tectonic transformation. Various reservoir spaces of pores, caves and fractures, with strong reservoir heterogeneity and diverse pore structures, have been developed. As a result, a quantitative description of the pore structure is difficult, and the accuracy of logging identification and prediction is low. These pose a lot of challenges to reservoir classification and evaluation as well as efficient development of the reservoirs. This study is based on the analysis of core, thin section, scanning electron microscope, high-pressure mercury injection and other data. Six types of petrophysical facies, PG1, PG2, PG3, PG4, PG5, and PG6, were divided according to the displacement pressure, mercury removal efficiency, and median pore-throat radius isobaric mercury parameters, combined with the shape of the capillary pressure curve. The petrophysical facies of the wells with mercury injection data were divided accordingly, and then the machine learning method was applied. The petrophysical facies division results of two mercury injection wells were used as training samples. The artificial neural network (ANN) method was applied to establish a training model of petrophysical facies recognition. Subsequently, the prediction for the petrophysical facies of each well in the oilfield was carried out, and the petrophysical facies division results of other mercury injection wells were applied to verify the prediction. The results show that the overall coincidence rate for identifying petrophysical facies is as high as 89.3%, which can be used for high-precision identification and prediction of petrophysical facies in non-coring wells." @default.
• W4297521545 created "2022-09-29" @default.
• W4297521545 creator A5007188437 @default.
• W4297521545 creator A5011333035 @default.
• W4297521545 creator A5012756702 @default.
• W4297521545 creator A5018411207 @default.
• W4297521545 creator A5038832637 @default.
• W4297521545 creator A5044176298 @default.
• W4297521545 creator A5071078406 @default.
• W4297521545 creator A5077125877 @default.
• W4297521545 creator A5079448948 @default.
• W4297521545 date "2022-09-28" @default.
• W4297521545 modified "2023-09-26" @default.
• W4297521545 title "Characterization and Evaluation of Carbonate Reservoir Pore Structure Based on Machine Learning" @default.
• W4297521545 cites W1511600599 @default.
• W4297521545 cites W1793048796 @default.
• W4297521545 cites W2015550612 @default.
• W4297521545 cites W2051787883 @default.
• W4297521545 cites W2062742099 @default.
• W4297521545 cites W2066067646 @default.
• W4297521545 cites W2070027332 @default.
• W4297521545 cites W2071640978 @default.
• W4297521545 cites W2073914501 @default.
• W4297521545 cites W2090856812 @default.
• W4297521545 cites W2303248233 @default.
• W4297521545 cites W2574035532 @default.
• W4297521545 cites W2760854451 @default.
• W4297521545 cites W2883318912 @default.
• W4297521545 cites W2888455867 @default.
• W4297521545 cites W3084539754 @default.
• W4297521545 cites W3093521266 @default.
• W4297521545 cites W3110612330 @default.
• W4297521545 cites W3124414187 @default.
• W4297521545 cites W3205606831 @default.
• W4297521545 cites W4206155535 @default.
• W4297521545 cites W4210936147 @default.
• W4297521545 cites W4294344022 @default.
• W4297521545 doi "https://doi.org/10.3390/en15197126" @default.
• W4297521545 hasPublicationYear "2022" @default.
• W4297521545 type Work @default.
• W4297521545 citedByCount "1" @default.
• W4297521545 countsByYear W42975215452023 @default.
• W4297521545 crossrefType "journal-article" @default.
• W4297521545 hasAuthorship W4297521545A5007188437 @default.
• W4297521545 hasAuthorship W4297521545A5011333035 @default.
• W4297521545 hasAuthorship W4297521545A5012756702 @default.
• W4297521545 hasAuthorship W4297521545A5018411207 @default.
• W4297521545 hasAuthorship W4297521545A5038832637 @default.
• W4297521545 hasAuthorship W4297521545A5044176298 @default.
• W4297521545 hasAuthorship W4297521545A5071078406 @default.
• W4297521545 hasAuthorship W4297521545A5077125877 @default.
• W4297521545 hasAuthorship W4297521545A5079448948 @default.
• W4297521545 hasBestOaLocation W42975215451 @default.
• W4297521545 hasConcept C105569014 @default.
• W4297521545 hasConcept C109007969 @default.
• W4297521545 hasConcept C114793014 @default.
• W4297521545 hasConcept C127313418 @default.
• W4297521545 hasConcept C14641988 @default.
• W4297521545 hasConcept C146588470 @default.
• W4297521545 hasConcept C187320778 @default.
• W4297521545 hasConcept C191897082 @default.
• W4297521545 hasConcept C192562407 @default.
• W4297521545 hasConcept C199289684 @default.
• W4297521545 hasConcept C2780659211 @default.
• W4297521545 hasConcept C46293882 @default.
• W4297521545 hasConcept C48797263 @default.
• W4297521545 hasConcept C5900021 @default.
• W4297521545 hasConcept C6648577 @default.
• W4297521545 hasConcept C78762247 @default.
• W4297521545 hasConceptScore W4297521545C105569014 @default.
• W4297521545 hasConceptScore W4297521545C109007969 @default.
• W4297521545 hasConceptScore W4297521545C114793014 @default.
• W4297521545 hasConceptScore W4297521545C127313418 @default.
• W4297521545 hasConceptScore W4297521545C14641988 @default.
• W4297521545 hasConceptScore W4297521545C146588470 @default.
• W4297521545 hasConceptScore W4297521545C187320778 @default.
• W4297521545 hasConceptScore W4297521545C191897082 @default.
• W4297521545 hasConceptScore W4297521545C192562407 @default.
• W4297521545 hasConceptScore W4297521545C199289684 @default.
• W4297521545 hasConceptScore W4297521545C2780659211 @default.
• W4297521545 hasConceptScore W4297521545C46293882 @default.
• W4297521545 hasConceptScore W4297521545C48797263 @default.
• W4297521545 hasConceptScore W4297521545C5900021 @default.
• W4297521545 hasConceptScore W4297521545C6648577 @default.
• W4297521545 hasConceptScore W4297521545C78762247 @default.
• W4297521545 hasIssue "19" @default.
• W4297521545 hasLocation W42975215451 @default.
• W4297521545 hasOpenAccess W4297521545 @default.
• W4297521545 hasPrimaryLocation W42975215451 @default.
• W4297521545 hasRelatedWork W1503249396 @default.
• W4297521545 hasRelatedWork W2070394625 @default.
• W4297521545 hasRelatedWork W2361110937 @default.
• W4297521545 hasRelatedWork W2390417528 @default.
• W4297521545 hasRelatedWork W2390518000 @default.
• W4297521545 hasRelatedWork W2749056975 @default.
• W4297521545 hasRelatedWork W2752601697 @default.
• W4297521545 hasRelatedWork W3203460338 @default.
• W4297521545 hasRelatedWork W4221098422 @default.

• next