{"title":"利用人工神经网络设计合成声波测井(SSL)的方法。科罗拉多油田应用","authors":"Carlos-Andrés Ayala Marín, Christiann-Camilo García-Yela","doi":"10.29047/01225383.242","DOIUrl":null,"url":null,"abstract":"A method that allows the creation of the Synthetic Sonic Log (SSL) was developed from the Spontaneous Potential (SP) logs, the resistivity logs of the flushed zone (SN), and the resistivity zone of the uninvaded zone (ILD), using Artificial Neural Networks (ANN). The SSL was obtained with the created tool calledGeneration of Synthetic Sonic Logs (GSSL). \nThe results obtained are presented hereinafter: in the Colorado 70 well, 90% of the generated SSL data present errors of less than 10%; in the Colorado 72 well; 53% of the SSL data obtained with the tool are below 5% error, in the Colorado 75 well, 80% of the SSL data present errors of less than 10%, and finally, the SSL generated for the Colorado 38 well follows the behavior of the original Sonic Logs of the well in an accurate manner. From the foregoing we conclude that the quality of the created tool is good and that the deviations are minimal in the times of transit of synthetic sonic profile.","PeriodicalId":55200,"journal":{"name":"Ct&f-Ciencia Tecnologia Y Futuro","volume":"2007 1","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2010-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Methodology to design of synthetic sonic log (SSL), using artificial neural networks. Colorado field application\",\"authors\":\"Carlos-Andrés Ayala Marín, Christiann-Camilo García-Yela\",\"doi\":\"10.29047/01225383.242\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A method that allows the creation of the Synthetic Sonic Log (SSL) was developed from the Spontaneous Potential (SP) logs, the resistivity logs of the flushed zone (SN), and the resistivity zone of the uninvaded zone (ILD), using Artificial Neural Networks (ANN). The SSL was obtained with the created tool calledGeneration of Synthetic Sonic Logs (GSSL). \\nThe results obtained are presented hereinafter: in the Colorado 70 well, 90% of the generated SSL data present errors of less than 10%; in the Colorado 72 well; 53% of the SSL data obtained with the tool are below 5% error, in the Colorado 75 well, 80% of the SSL data present errors of less than 10%, and finally, the SSL generated for the Colorado 38 well follows the behavior of the original Sonic Logs of the well in an accurate manner. From the foregoing we conclude that the quality of the created tool is good and that the deviations are minimal in the times of transit of synthetic sonic profile.\",\"PeriodicalId\":55200,\"journal\":{\"name\":\"Ct&f-Ciencia Tecnologia Y Futuro\",\"volume\":\"2007 1\",\"pages\":\"\"},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2010-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ct&f-Ciencia Tecnologia Y Futuro\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.29047/01225383.242\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ct&f-Ciencia Tecnologia Y Futuro","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.29047/01225383.242","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Methodology to design of synthetic sonic log (SSL), using artificial neural networks. Colorado field application
A method that allows the creation of the Synthetic Sonic Log (SSL) was developed from the Spontaneous Potential (SP) logs, the resistivity logs of the flushed zone (SN), and the resistivity zone of the uninvaded zone (ILD), using Artificial Neural Networks (ANN). The SSL was obtained with the created tool calledGeneration of Synthetic Sonic Logs (GSSL).
The results obtained are presented hereinafter: in the Colorado 70 well, 90% of the generated SSL data present errors of less than 10%; in the Colorado 72 well; 53% of the SSL data obtained with the tool are below 5% error, in the Colorado 75 well, 80% of the SSL data present errors of less than 10%, and finally, the SSL generated for the Colorado 38 well follows the behavior of the original Sonic Logs of the well in an accurate manner. From the foregoing we conclude that the quality of the created tool is good and that the deviations are minimal in the times of transit of synthetic sonic profile.
期刊介绍:
The objective of CT&F is to publish the achievements of scientific research and technological developments of Ecopetrol S.A. and the research of other institutions in the field of oil, gas and alternative energy sources.
CT&F welcomes original, novel and high-impact contributions from all the fields in the oil and gas industry like: Acquisition and Exploration technologies, Basins characterization and modeling, Petroleum geology, Reservoir modeling, Enhanced Oil Recovery Technologies, Unconventional resources, Petroleum refining, Petrochemistry, Upgrading technologies, Technologies for fuels quality, Process modeling, and optimization, Supply chain optimization, Biofuels, Renewable energies.