Performance of evolutionary optimized machine learning for modeling total organic carbon in core samples of shale gas fields
Leonardo Goliatt, Camila Martins Saporetti, L. C. Oliveira, Egberto Pereira
Journal
- ISSN / E-ISSN
- — / —
- DOI
- 10.1016/j.petlm.2023.05.005 ↗
- Volume · Issue · Pages
- 10 · 1 · 150-164
- Publisher
- KeAi Communications Co.
- Article URL
- https://doi.org/10.1016/j.petlm.2023.05.005 ↗
- Article details
- Unverified
Publication date (each date has its type and source)
02 Jun 2023
OpenAlex publication date · source: OpenAlex
| Type | Date | Source |
|---|---|---|
| OpenAlex publication date | 02 Jun 2023 | OpenAlex |
Keywords (as given): total organic carbon prediction; shale gas; drill core sample; metaheuristic optimization; extreme learning machine; genetic algorithm; differential evolution; particle swarm optimization; grey wolf optimizer; artificial bee colony algorithm; evolution strategies; Sichuan Basin; hybrid machine learning
HEC Status at Publication Not the journal's current status
HEC Status at PublicationConclusive
HEC status at publication
Recognized
X
Based on the recorded HEC dataset applicable to the article's publication date. Listed as X in the HEC list for 2022–23.
- Journal
- Petroleum
- Publication date used
- 02 Jun 2023 (OpenAlex publication date)
- Applicable HEC period
- 2022–23 (version 2) · 01 Jul 2022 – 30 Jun 2023
- Category
- X
- Recognition status
- Recognized (OK_RECORD_FOUND)
- Source
- hjrs-2022-23 row 10001
- Verification status
- Verified against source · last verified 16 Oct 2026
This is an automatically generated summary based on the information available on the publication date. Terms & conditions apply.