Reconhecimentos de fácies em perfil com rede neural competitiva
The recognition of sedimentary facies in a depositional system has a key role in formation evaluation to perform the characterization of an oil system. In the absence of these facies description by cores or outcrop, we present a methodology based on intelligent algorithm able to identify one facies...
| Autor principal: | COSTA, Jéssica Lia Santos da |
|---|---|
| Grau: | Trabalho de Conclusão de Curso - Graduação |
| Publicado em: |
2020
|
| Assuntos: | |
| Acesso em linha: |
https://bdm.ufpa.br/jspui/handle/prefix/2700 |
| Resumo: |
|---|
|
The recognition of sedimentary facies in a depositional system has a key role in formation evaluation to perform the characterization of an oil system. In the absence of these facies description by cores or outcrop, we present a methodology based on intelligent algorithm able to identify one facies of interest in wireline logs. This methodology uses a competitive neural network to extract geological information from the physical properties mapped in the M-N plot. The competition among neurons identifies the facies of interest, which has been previously identified in a cored borehole, in other non cored boreholes in an oil field. The purpose of this methodology is to encode and transmit the geological information gained in cored boreholes to non cored wells and thus achieve the geological interpretation of one layer in an oil field. This methodology has been evaluated using synthetic data and actual wireline logs from two boreholes drilled in the Namorado oil field, Campos Basin, Brazil. |