首页> 外文学位 >Interpretation and Fracture Characterization of Early-Cretaceous Buda Limestone Formation Using Post-Stack 3D Seismic Data in Zavala County, Texas
【24h】

Interpretation and Fracture Characterization of Early-Cretaceous Buda Limestone Formation Using Post-Stack 3D Seismic Data in Zavala County, Texas

机译:利用叠后3D地震数据在得克萨斯州扎瓦拉县解释早白垩世布达石灰岩地层和断裂特征

获取原文
获取原文并翻译 | 示例

摘要

The Buda Limestone is a naturally fractured Early Cretaceous carbonate formation in south Texas which unconformably underlies the Eagle Ford Shale. Matrix porosity of the Buda is less than 6%, therefore natural fractures improve the potential for commercial hydrocarbon production from this tight limestone formation. This presents a challenge for producers to identify these zones using well log and post stack 3D seismic data typically available to medium or small exploration companies. This project provides a workflow based on well log analysis tied to seismic acoustic impedance (AI) inversion to locate areas of probable natural fractures.;Acoustic impedance inversion was performed across a 42 square mile 3D seismic survey. The AI data shows low AI shadow zones on the down thrown side of faults. Post stack geometric seismic attributes such as coherence, maximum and minimum curvature were analyzed in the anomalous AI areas, along with physical seismic attributes such as instantaneous amplitude and instantaneous frequency. This study indicates that a combination of acoustic impedance inversion and seismic attributes can identify areas of enhanced natural fracturing within the Buda Limestone interval.
机译:布达(Buda)石灰石是德克萨斯州南部天然裂缝性的早白垩世碳酸盐岩地层,不整合地存在于Eagle Ford页岩之下。布达的基质孔隙度小于6%,因此,天然裂缝可改善这种致密石灰岩地层的商业化烃生产潜力。这给生产者使用测井和叠后3D地震数据(通常适用于中小型勘探公司)识别这些区域带来了挑战。该项目提供了基于与地震声阻抗(AI)反演相关的测井分析的工作流程,以定位可能的天然裂缝区域;在42平方英里的3D地震勘测中进行了声阻抗反演。 AI数据在故障的向下投射侧显示出较低的AI阴影区域。分析了异常AI区域中的叠后几何地震属性,例如相干性,最大曲率和最小曲率,以及物理地震属性,例如瞬时振幅和瞬时频率。这项研究表明,声阻抗反演和地震属性的组合可以识别布达石灰岩层段内自然裂缝增加的区域。

著录项

  • 作者单位

    University of Arkansas.;

  • 授予单位 University of Arkansas.;
  • 学科 Geophysics.;Geology.
  • 学位 M.S.
  • 年度 2018
  • 页码 66 p.
  • 总页数 66
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号