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

IF 0.5 4区工程技术 Q4 ENERGY & FUELS

Ct&f-Ciencia Tecnologia Y Futuro Pub Date : 2010-07-01 DOI:10.29047/01225383.242

Carlos-Andrés Ayala Marín, Christiann-Camilo García-Yela

{"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}

引用次数: 3

摘要

利用人工神经网络(ANN)，利用自然电位(SP)测井、冲刷层(SN)的电阻率测井和未侵层(ILD)的电阻率测井，开发了一种合成声波测井(SSL)的方法。SSL是通过创建的合成声波测井生成工具(GSSL)获得的。结果如下:在Colorado 70井中，90%生成的SSL数据误差小于10%;科罗拉多72号井;使用该工具获得的SSL数据中，53%的数据误差小于5%，在Colorado 75井中，80%的SSL数据误差小于10%，最后，Colorado 38井生成的SSL数据准确地遵循了该井原始声波测井的行为。从上述我们得出的结论是，所创建的工具的质量是好的，并且偏差是最小的时间在合成声波剖面的过境。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

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.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Ct&f-Ciencia Tecnologia Y Futuro Energy-General Energy

CiteScore

1.50

自引率

0.00%

发文量

审稿时长

>12 weeks

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.