Evaluation Method of Reservoir Heterogeneity Based on Neural Network Technology Article Swipe
Shasha Yang
,
Ying Chen
,
Yong Yang
,
Kekuo Yuan
,
Juanjuan Quan
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/2066/1/012047
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/2066/1/012047
Reservoir is the underground storage and accumulation place of oil and natural gas. The accuracy of reservoir heterogeneity evaluation has great economic value for correctly guiding the production and development of oil and natural gas. The high-order neural network method is used to comprehensively evaluate the heterogeneity of the reservoir. This method was applied to the evaluation of reservoir heterogeneity in the PK area. The results show that the heterogeneity of sandy clastic flow sand bodies is the weakest, the sandy landslide sand bodies are medium, and the turbidity current sand bodies are strongest. The evaluation method of reservoir heterogeneity based on high-order neural network technology effectively solves the problem of inconsistent conclusions of single-parameter evaluation of heterogeneity in conventional methods, and can quantitatively characterize the degree of reservoir heterogeneity.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1742-6596/2066/1/012047
- https://iopscience.iop.org/article/10.1088/1742-6596/2066/1/012047/pdf
- OA Status
- diamond
- Cited By
- 2
- References
- 9
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3213649910
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3213649910Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1088/1742-6596/2066/1/012047Digital Object Identifier
- Title
-
Evaluation Method of Reservoir Heterogeneity Based on Neural Network TechnologyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-11-01Full publication date if available
- Authors
-
Shasha Yang, Ying Chen, Yong Yang, Kekuo Yuan, Juanjuan QuanList of authors in order
- Landing page
-
https://doi.org/10.1088/1742-6596/2066/1/012047Publisher landing page
- PDF URL
-
https://iopscience.iop.org/article/10.1088/1742-6596/2066/1/012047/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://iopscience.iop.org/article/10.1088/1742-6596/2066/1/012047/pdfDirect OA link when available
- Concepts
-
Petroleum engineering, Artificial neural network, Evaluation methods, Geology, Spatial heterogeneity, Environmental science, Computer science, Artificial intelligence, Engineering, Ecology, Reliability engineering, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
9Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3213649910 |
|---|---|
| doi | https://doi.org/10.1088/1742-6596/2066/1/012047 |
| ids.doi | https://doi.org/10.1088/1742-6596/2066/1/012047 |
| ids.mag | 3213649910 |
| ids.openalex | https://openalex.org/W3213649910 |
| fwci | 0.17269191 |
| type | article |
| title | Evaluation Method of Reservoir Heterogeneity Based on Neural Network Technology |
| biblio.issue | 1 |
| biblio.volume | 2066 |
| biblio.last_page | 012047 |
| biblio.first_page | 012047 |
| topics[0].id | https://openalex.org/T13050 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.9973999857902527 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2212 |
| topics[0].subfield.display_name | Ocean Engineering |
| topics[0].display_name | Oil and Gas Production Techniques |
| topics[1].id | https://openalex.org/T11801 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.986299991607666 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2212 |
| topics[1].subfield.display_name | Ocean Engineering |
| topics[1].display_name | Reservoir Engineering and Simulation Methods |
| topics[2].id | https://openalex.org/T14470 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9771999716758728 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2207 |
| topics[2].subfield.display_name | Control and Systems Engineering |
| topics[2].display_name | Advanced Data Processing Techniques |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C78762247 |
| concepts[0].level | 1 |
| concepts[0].score | 0.6476369500160217 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q1273174 |
| concepts[0].display_name | Petroleum engineering |
| concepts[1].id | https://openalex.org/C50644808 |
| concepts[1].level | 2 |
| concepts[1].score | 0.5097226500511169 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q192776 |
| concepts[1].display_name | Artificial neural network |
| concepts[2].id | https://openalex.org/C3018395757 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5007495880126953 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q1379672 |
| concepts[2].display_name | Evaluation methods |
| concepts[3].id | https://openalex.org/C127313418 |
| concepts[3].level | 0 |
| concepts[3].score | 0.49024325609207153 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q1069 |
| concepts[3].display_name | Geology |
| concepts[4].id | https://openalex.org/C180478619 |
| concepts[4].level | 2 |
| concepts[4].score | 0.41730231046676636 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q7574066 |
| concepts[4].display_name | Spatial heterogeneity |
| concepts[5].id | https://openalex.org/C39432304 |
| concepts[5].level | 0 |
| concepts[5].score | 0.3378908634185791 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q188847 |
| concepts[5].display_name | Environmental science |
| concepts[6].id | https://openalex.org/C41008148 |
| concepts[6].level | 0 |
| concepts[6].score | 0.2477644681930542 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[6].display_name | Computer science |
| concepts[7].id | https://openalex.org/C154945302 |
| concepts[7].level | 1 |
| concepts[7].score | 0.1337011456489563 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[7].display_name | Artificial intelligence |
| concepts[8].id | https://openalex.org/C127413603 |
| concepts[8].level | 0 |
| concepts[8].score | 0.08285456895828247 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[8].display_name | Engineering |
| concepts[9].id | https://openalex.org/C18903297 |
| concepts[9].level | 1 |
| concepts[9].score | 0.0811457633972168 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q7150 |
| concepts[9].display_name | Ecology |
| concepts[10].id | https://openalex.org/C200601418 |
| concepts[10].level | 1 |
| concepts[10].score | 0.0 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q2193887 |
| concepts[10].display_name | Reliability engineering |
| concepts[11].id | https://openalex.org/C86803240 |
| concepts[11].level | 0 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[11].display_name | Biology |
| keywords[0].id | https://openalex.org/keywords/petroleum-engineering |
| keywords[0].score | 0.6476369500160217 |
| keywords[0].display_name | Petroleum engineering |
| keywords[1].id | https://openalex.org/keywords/artificial-neural-network |
| keywords[1].score | 0.5097226500511169 |
| keywords[1].display_name | Artificial neural network |
| keywords[2].id | https://openalex.org/keywords/evaluation-methods |
| keywords[2].score | 0.5007495880126953 |
| keywords[2].display_name | Evaluation methods |
| keywords[3].id | https://openalex.org/keywords/geology |
| keywords[3].score | 0.49024325609207153 |
| keywords[3].display_name | Geology |
| keywords[4].id | https://openalex.org/keywords/spatial-heterogeneity |
| keywords[4].score | 0.41730231046676636 |
| keywords[4].display_name | Spatial heterogeneity |
| keywords[5].id | https://openalex.org/keywords/environmental-science |
| keywords[5].score | 0.3378908634185791 |
| keywords[5].display_name | Environmental science |
| keywords[6].id | https://openalex.org/keywords/computer-science |
| keywords[6].score | 0.2477644681930542 |
| keywords[6].display_name | Computer science |
| keywords[7].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[7].score | 0.1337011456489563 |
| keywords[7].display_name | Artificial intelligence |
| keywords[8].id | https://openalex.org/keywords/engineering |
| keywords[8].score | 0.08285456895828247 |
| keywords[8].display_name | Engineering |
| keywords[9].id | https://openalex.org/keywords/ecology |
| keywords[9].score | 0.0811457633972168 |
| keywords[9].display_name | Ecology |
| language | en |
| locations[0].id | doi:10.1088/1742-6596/2066/1/012047 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210187594 |
| locations[0].source.issn | 1742-6588, 1742-6596 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1742-6588 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | Journal of Physics Conference Series |
| locations[0].source.host_organization | https://openalex.org/P4310320083 |
| locations[0].source.host_organization_name | IOP Publishing |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320083, https://openalex.org/P4310311669 |
| locations[0].source.host_organization_lineage_names | IOP Publishing, Institute of Physics |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://iopscience.iop.org/article/10.1088/1742-6596/2066/1/012047/pdf |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Journal of Physics: Conference Series |
| locations[0].landing_page_url | https://doi.org/10.1088/1742-6596/2066/1/012047 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5112388002 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Shasha Yang |
| authorships[0].countries | CN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4210162994 |
| authorships[0].affiliations[0].raw_affiliation_string | School of Civil Engineering, XiJing University, Xi'an, Shaanxi, 610500, China |
| authorships[0].institutions[0].id | https://openalex.org/I4210162994 |
| authorships[0].institutions[0].ror | https://ror.org/05xsjkb63 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I4210162994 |
| authorships[0].institutions[0].country_code | CN |
| authorships[0].institutions[0].display_name | Xijing University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Shasha Yang |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | School of Civil Engineering, XiJing University, Xi'an, Shaanxi, 610500, China |
| authorships[1].author.id | https://openalex.org/A5115602925 |
| authorships[1].author.orcid | https://orcid.org/0009-0009-1507-3636 |
| authorships[1].author.display_name | Ying Chen |
| authorships[1].countries | CN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I4210162188 |
| authorships[1].affiliations[0].raw_affiliation_string | Zhidan Oil Production Plant, Shaanxi Yanchang Petroleum (Group) Co. Ltd., Yan'an, Shaanxi, 716000, China |
| authorships[1].institutions[0].id | https://openalex.org/I4210162188 |
| authorships[1].institutions[0].ror | https://ror.org/05crb7x25 |
| authorships[1].institutions[0].type | company |
| authorships[1].institutions[0].lineage | https://openalex.org/I4210162188 |
| authorships[1].institutions[0].country_code | CN |
| authorships[1].institutions[0].display_name | Shaanxi Yanchang Petroleum (China) |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Ying Chen |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Zhidan Oil Production Plant, Shaanxi Yanchang Petroleum (Group) Co. Ltd., Yan'an, Shaanxi, 716000, China |
| authorships[2].author.id | https://openalex.org/A5014343452 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Yong Yang |
| authorships[2].countries | CN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I4210162188 |
| authorships[2].affiliations[0].raw_affiliation_string | Fuxian Oil Production Plant, Shaanxi Yanchang Petroleum (Group) Co. Ltd., Yan'an, Shaanxi, 727500, China |
| authorships[2].institutions[0].id | https://openalex.org/I4210162188 |
| authorships[2].institutions[0].ror | https://ror.org/05crb7x25 |
| authorships[2].institutions[0].type | company |
| authorships[2].institutions[0].lineage | https://openalex.org/I4210162188 |
| authorships[2].institutions[0].country_code | CN |
| authorships[2].institutions[0].display_name | Shaanxi Yanchang Petroleum (China) |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Yong Yang |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Fuxian Oil Production Plant, Shaanxi Yanchang Petroleum (Group) Co. Ltd., Yan'an, Shaanxi, 727500, China |
| authorships[3].author.id | https://openalex.org/A5110851816 |
| authorships[3].author.orcid | |
| authorships[3].author.display_name | Kekuo Yuan |
| authorships[3].countries | CN |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I4210162994 |
| authorships[3].affiliations[0].raw_affiliation_string | School of Civil Engineering, XiJing University, Xi'an, Shaanxi, 610500, China |
| authorships[3].institutions[0].id | https://openalex.org/I4210162994 |
| authorships[3].institutions[0].ror | https://ror.org/05xsjkb63 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I4210162994 |
| authorships[3].institutions[0].country_code | CN |
| authorships[3].institutions[0].display_name | Xijing University |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Kekuo Yuan |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | School of Civil Engineering, XiJing University, Xi'an, Shaanxi, 610500, China |
| authorships[4].author.id | https://openalex.org/A5073466582 |
| authorships[4].author.orcid | |
| authorships[4].author.display_name | Juanjuan Quan |
| authorships[4].countries | CN |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I4210162994 |
| authorships[4].affiliations[0].raw_affiliation_string | School of Civil Engineering, XiJing University, Xi'an, Shaanxi, 610500, China |
| authorships[4].institutions[0].id | https://openalex.org/I4210162994 |
| authorships[4].institutions[0].ror | https://ror.org/05xsjkb63 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I4210162994 |
| authorships[4].institutions[0].country_code | CN |
| authorships[4].institutions[0].display_name | Xijing University |
| authorships[4].author_position | last |
| authorships[4].raw_author_name | Juanjuan Quan |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | School of Civil Engineering, XiJing University, Xi'an, Shaanxi, 610500, China |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://iopscience.iop.org/article/10.1088/1742-6596/2066/1/012047/pdf |
| open_access.oa_status | diamond |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Evaluation Method of Reservoir Heterogeneity Based on Neural Network Technology |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T13050 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.9973999857902527 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2212 |
| primary_topic.subfield.display_name | Ocean Engineering |
| primary_topic.display_name | Oil and Gas Production Techniques |
| related_works | https://openalex.org/W2324615561, https://openalex.org/W2086120259, https://openalex.org/W2245170124, https://openalex.org/W2076393078, https://openalex.org/W3186982001, https://openalex.org/W2137941439, https://openalex.org/W1984402782, https://openalex.org/W1999913942, https://openalex.org/W2004200960, https://openalex.org/W1999891779 |
| cited_by_count | 2 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| counts_by_year[1].year | 2022 |
| counts_by_year[1].cited_by_count | 1 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1088/1742-6596/2066/1/012047 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210187594 |
| best_oa_location.source.issn | 1742-6588, 1742-6596 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1742-6588 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | Journal of Physics Conference Series |
| best_oa_location.source.host_organization | https://openalex.org/P4310320083 |
| best_oa_location.source.host_organization_name | IOP Publishing |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320083, https://openalex.org/P4310311669 |
| best_oa_location.source.host_organization_lineage_names | IOP Publishing, Institute of Physics |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://iopscience.iop.org/article/10.1088/1742-6596/2066/1/012047/pdf |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Journal of Physics: Conference Series |
| best_oa_location.landing_page_url | https://doi.org/10.1088/1742-6596/2066/1/012047 |
| primary_location.id | doi:10.1088/1742-6596/2066/1/012047 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210187594 |
| primary_location.source.issn | 1742-6588, 1742-6596 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1742-6588 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | Journal of Physics Conference Series |
| primary_location.source.host_organization | https://openalex.org/P4310320083 |
| primary_location.source.host_organization_name | IOP Publishing |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320083, https://openalex.org/P4310311669 |
| primary_location.source.host_organization_lineage_names | IOP Publishing, Institute of Physics |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://iopscience.iop.org/article/10.1088/1742-6596/2066/1/012047/pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Journal of Physics: Conference Series |
| primary_location.landing_page_url | https://doi.org/10.1088/1742-6596/2066/1/012047 |
| publication_date | 2021-11-01 |
| publication_year | 2021 |
| referenced_works | https://openalex.org/W3144409608, https://openalex.org/W3130284467, https://openalex.org/W3123090417, https://openalex.org/W3126016746, https://openalex.org/W6769629676, https://openalex.org/W2964822258, https://openalex.org/W6771019269, https://openalex.org/W2980551306, https://openalex.org/W2994281675 |
| referenced_works_count | 9 |
| abstract_inverted_index.PK | 63 |
| abstract_inverted_index.in | 61, 119 |
| abstract_inverted_index.is | 2, 41, 77 |
| abstract_inverted_index.of | 9, 16, 31, 48, 58, 71, 98, 111, 114, 117, 128 |
| abstract_inverted_index.on | 102 |
| abstract_inverted_index.to | 43, 55 |
| abstract_inverted_index.The | 14, 36, 65, 95 |
| abstract_inverted_index.and | 6, 11, 29, 33, 87, 122 |
| abstract_inverted_index.are | 85, 93 |
| abstract_inverted_index.can | 123 |
| abstract_inverted_index.for | 24 |
| abstract_inverted_index.has | 20 |
| abstract_inverted_index.oil | 10, 32 |
| abstract_inverted_index.the | 3, 27, 46, 49, 56, 62, 69, 78, 80, 88, 109, 126 |
| abstract_inverted_index.was | 53 |
| abstract_inverted_index.This | 51 |
| abstract_inverted_index.flow | 74 |
| abstract_inverted_index.gas. | 13, 35 |
| abstract_inverted_index.sand | 75, 83, 91 |
| abstract_inverted_index.show | 67 |
| abstract_inverted_index.that | 68 |
| abstract_inverted_index.used | 42 |
| abstract_inverted_index.area. | 64 |
| abstract_inverted_index.based | 101 |
| abstract_inverted_index.great | 21 |
| abstract_inverted_index.place | 8 |
| abstract_inverted_index.sandy | 72, 81 |
| abstract_inverted_index.value | 23 |
| abstract_inverted_index.bodies | 76, 84, 92 |
| abstract_inverted_index.degree | 127 |
| abstract_inverted_index.method | 40, 52, 97 |
| abstract_inverted_index.neural | 38, 104 |
| abstract_inverted_index.solves | 108 |
| abstract_inverted_index.applied | 54 |
| abstract_inverted_index.clastic | 73 |
| abstract_inverted_index.current | 90 |
| abstract_inverted_index.guiding | 26 |
| abstract_inverted_index.medium, | 86 |
| abstract_inverted_index.natural | 12, 34 |
| abstract_inverted_index.network | 39, 105 |
| abstract_inverted_index.problem | 110 |
| abstract_inverted_index.results | 66 |
| abstract_inverted_index.storage | 5 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.accuracy | 15 |
| abstract_inverted_index.economic | 22 |
| abstract_inverted_index.evaluate | 45 |
| abstract_inverted_index.methods, | 121 |
| abstract_inverted_index.weakest, | 79 |
| abstract_inverted_index.Reservoir | 1 |
| abstract_inverted_index.correctly | 25 |
| abstract_inverted_index.landslide | 82 |
| abstract_inverted_index.reservoir | 17, 59, 99, 129 |
| abstract_inverted_index.turbidity | 89 |
| abstract_inverted_index.evaluation | 19, 57, 96, 116 |
| abstract_inverted_index.high-order | 37, 103 |
| abstract_inverted_index.production | 28 |
| abstract_inverted_index.reservoir. | 50 |
| abstract_inverted_index.strongest. | 94 |
| abstract_inverted_index.technology | 106 |
| abstract_inverted_index.conclusions | 113 |
| abstract_inverted_index.development | 30 |
| abstract_inverted_index.effectively | 107 |
| abstract_inverted_index.underground | 4 |
| abstract_inverted_index.accumulation | 7 |
| abstract_inverted_index.characterize | 125 |
| abstract_inverted_index.conventional | 120 |
| abstract_inverted_index.inconsistent | 112 |
| abstract_inverted_index.heterogeneity | 18, 47, 60, 70, 100, 118 |
| abstract_inverted_index.heterogeneity. | 130 |
| abstract_inverted_index.quantitatively | 124 |
| abstract_inverted_index.comprehensively | 44 |
| abstract_inverted_index.single-parameter | 115 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile.value | 0.52480291 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |