Research on Oil and Gas-Bearing Zone Prediction and Identification Based on the SVD–K-Means Algorithm—A Case Study of the WZ6-1 Oil-Bearing Structure in the Beibu Gulf Basin, South China Sea
Energies, ISSN: 1996-1073, Vol: 17, Issue: 22
2024
- 2Mentions
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Mentions2
- Blog Mentions1
- Blog1
- News Mentions1
- News1
Most Recent News
Research from Zhejiang Ocean University in the Area of Algorithms Described (Research on Oil and Gas-Bearing Zone Prediction and Identification Based on the SVD-K-Means Algorithm-A Case Study of the WZ6-1 Oil-Bearing Structure in the Beibu Gulf ...)
2024 DEC 09 (NewsRx) -- By a News Reporter-Staff News Editor at Energy Daily News -- Data detailed on algorithms have been presented. According to
Article Description
The WZ6-1 oil-bearing structure in the Beibu Gulf Basin of the South China Sea has well-developed faults with significant variations in fault sealing capacity, resulting in a complex and highly variable distribution of oil, gas, and water, and limited understanding of hydrocarbon accumulation patterns. Traditional methods, such as single seismic attributes and linear fusion of multiple seismic attributes, have proven ineffective in identifying and predicting oil and gas-bearing areas in this region, leading to five unsuccessful wells. Through comprehensive analysis of drilled wells and seismic data, six types of horizon seismic attributes were selected. A novel approach for predicting oil-bearing zones was proposed, employing SVD–K-means nonlinear clustering for multiple seismic attribute fusion. The application results indicate: ① Singular value decomposition (SVD) technology not only reduces the correlation redundancy among seismic attribute data variables, but enables data dimensionality reduction and noise suppression, decreasing ambiguity in prediction results and enhancing reliability. ② The K-means nonlinear clustering method facilitates the nonlinear fusion of multiple seismic attribute parameters, effectively uncovering the nonlinear features of the underlying relationship between seismic attributes and reservoir oil-bearing characteristics, thereby amplifying the hydrocarbon information within the seismic attribute variables. ③ Compared to K-means, SVD–K-means demonstrates superior performance across all metrics, with an 18.4% increase in the SC coefficient, a 57.8% increase in the CH index, and a 24.7% improvement in the DB index. ④ The results of oil-bearing zone prediction using the SVD–K-means algorithm align well with the drilling outcomes in the study area and correspond to the geological patterns of hydrocarbon enrichment in this region. This has been confirmed by the high-yield industrial oil flow obtained from the newly drilled WZ6-1-A3 well. The SVD–K-means algorithm for predicting oil and gas-bearing zones provides a new approach for predicting hydrocarbon-rich areas in complex fault block structures with limited drilling and poor-quality seismic data.
Bibliographic Details
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know