示范研究:采用数据管理方法进行油气开采:面向未来的框架

Michael F. Curran, Ben Wolff, P. Stahl
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引用次数: 8

摘要

构建了一个数据库框架,目的是通过编译油气区块的回收数据来确定成功的恢复实践,从而创建恢复决策管理工具。预先存在的数据来自怀俄明州大绿河盆地的两个生产油田:Jonah Infill和Moxa Arch的公共和私人数据库。该框架包括复垦实践测量表(例如,土壤处理方法和修正,播种混合和时间,杂草管理),地理和气候数据(例如,降水,坡度,坡向,海拔和温度)和监测数据(例如,植被组成和结构以及土壤分析和放牧)。采用Microsoft Access和ESRI ArcGIS建立复垦数据库,实现数据的一致、可靠的存储、操作和检索。该项目的短期目标是量化干扰和填海努力,并评估单个井台的填海状况。该项目的长期目标是提供:(1)分析和隔离导致填海成功和失败的趋势的操作框架;(2)在可变环境条件下限制不确定性和估计相关风险的强大决策管理工具;(3)评估填海监管标准;(4)提供灵活和可共享的数据库,允许从不同来源输入额外的数据。发现数据库性能依赖于数据一致性和有效性。查询已填充的数据以及统一导入的数据揭示了数据库框架的多个优点和缺点。额外的
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DEMONSTRATION STUDY: Approaching oil and gas pad reclamation with data management: A framework for the future
A database framework was constructed with the purpose of creating a restoration decision management tool by compiling oil and gas pad reclamation data to identify successful restoration practices. Pre-existing data were secured from public and private databases from two Wyoming production fields in the Greater Green River Basin: Jonah Infill and Moxa Arch. The framework includes tables for measurements of reclamation practices (e.g., soil handling methods and amendments, seeding mix and timing, and weed management), geographical and climate data (e.g., precipitation, slope, aspect, elevation, and temperature) and monitoring data (e.g., vegetation composition and structure along with soil analysis and grazing). Microsoft Access and ESRI ArcGIS were employed to build the reclamation database for consistent and reliable data storage, manipulation, and retrieval. Short-term goals of the project were to quantify disturbance and reclamation efforts and to evaluate the reclamation status of individual well pads. Long-term goals of the project are to deliver: (1) an operational framework to analyze and isolate trends leading to reclamation success and failure, (2) a strong decision management tool for limiting uncertainty and estimating associated risk under variable environmental conditions, (3) to evaluate regulatory standards for reclamation, and (4) to offer a flexible and sharable database that allows for additional data input from diverse sources. Database performance was found to be dependent on data consistency and validity. Querying populated data along with uniting imported data has revealed multiple strengths and weaknesses with the database framework. Additional
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