| Full text | |
| Author(s): |
Ribeiro, Luiz C. F.
[1]
;
Afonso, Luis C. S.
[2]
;
Colombo, Danilo
[3]
;
Guilherme, Ivan R.
[4]
;
Papa, Joao P.
[1]
Total Authors: 5
|
| Affiliation: | [1] UNESP Sao Paulo State Univ, Sch Sci, Sao Paulo - Brazil
[2] UFSCar Fed Univ Sao Carlos, Dept Comp, Sao Carlos - Brazil
[3] Cenpes Petroleo Brasileiro SA, Rio De Janeiro - Brazil
[4] UNESP Sao Paulo State Univ, Inst Geosci & Exact Sci, Sao Paulo - Brazil
Total Affiliations: 4
|
| Document type: | Journal article |
| Source: | JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING; v. 187, APR 2020. |
| Web of Science Citations: | 0 |
| Abstract | |
Oil and gas prospecting is an important economic activity, besides being expensive and quite complex, thus requiring close monitoring to avoid work accidents and mainly environmental damages. An essential source of information concerns the daily drilling reports that contain operations technical interpretations and additional information from rig sensors. However, only a few works have focused on mining textual information from such reports for providing intelligent-based decision-making mechanisms to aid safety and efficiency concerns in drilling operations. This work proposes a contextual-driven approach based on Recurrent Neural Networks to recognize events in drilling reports that can outperform other related techniques. We also introduce a novel approach based on evolutionary computing to combine partially trained models using cyclical learning rates. Experiments conducted on two unbalanced datasets provided by Petrobras (Petroleo Brasileiro S.A.) show that our model improved Macro-F1 scores over the baseline by more than 47%. Besides, the proposed ensembling technique further enhanced these values by another 3% in the best scenario. Such promising results can shed light over new research directions in the field.(1) (AU) | |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 16/19403-6 - Energy-based learning models and their applications |
| Grantee: | João Paulo Papa |
| Support Opportunities: | Regular Research Grants |