Implementing Business Analytics Tool to Optimize Deep Shale Gas Drilling Operations: A Visualization Approach to Analyze Drilling Performance

Author:

Chen Lu1,Yan Juntao2,Liu Jie3,Liang Yanchao3,Li Wei1,Qi Peng1,Baojian Hao4,Guangzhi Shi4,Tian Peng3,Yang Bo3,Liu Bingqi1,Xu Ziyuan1,Yang Zhigang2

Affiliation:

1. SLB Beijing Geoscience Center, Beijing, P.R. China

2. PetroChina Chongqing Shale Gas Exploration and Development Co., Ltd., Chongqing, P.R. China

3. SLB China Services, Chengdu, Sichuan, P.R. China

4. CNPC, Oman Exploration and Development Department, Muscat, Oman

Abstract

Abstract Our work combines a business analytics intelligence tool with advanced big data management techniques, and applied the tool to drilling performance analysis and decision-making processes for deep shale gas operations. An advanced data processing workflow including transforming and mapping data was designed and implemented to unify current and historical drilling operations data into a unique dataset. The latest operations information is regularly collected and updated through an automated data querying process, which saves the effort of repeating data wrangling manually and eliminates the risk of human error. A business intelligence (BI) tool is used to promote the engineering of the data analytics process, create relevant key performance indicators, design data models, and establish a tracking and evaluation system. Finally, the BI visualization tool is used to generate and publish comprehensive cloud-based dashboards and reports. The BI visualization dashboard enables oilfield companies to perform efficient and accurate analysis of drilling performance. The BI tool allows Effective identification of rotary steerable system (RSS) utilization, drilling efficiency, failures, and downhole applicable conditions on basis of real job data, thereby enabling informed RSS management decisions Clarification of high performance of the RSS for making strategic decisions for high profile jobs Classification of rotary steerable tool failures, nonproductive time trends and monitoring maintenance strategies to reduce failures that have a major impact on drilling operations performance Incorporation of real-time operational data and detection of record-breaking jobs Development of custom drilling operations performance reports Reducing the workload for data collection and chart making with faster acquisition of more accurate data than with previous methods Customized and accurate documentation of drilling performance data in a consistent and standardized fashion Publishing of specific guidelines for RSS applications in deep shale gas drilling Performing technical analysis for operators The integration of BI tools in drilling operations is a step change in how service companies and oilfield companies are analyzing and monitoring operation performance (efficiency and quality) to optimize drilling and minimize costs. BI analysis using existing techniques and resources was conducted for a dataset from more than 100 wells with over 1,000 runs in a Sichuan basin deep shale gas field.

Publisher

SPE

Reference7 articles.

1. Barakat, M., Abu El Ela, M., and Khalaf, F. 2021. Integrating risk management concepts into the drilling non-productive time. Journal of Petroleum Exploration and Production Technology11: 887-900. https://doi.org/10.1007/s13202-020-01059-0.

2. Becker, L. T. and Gould, E. M. 2019. Microsoft Power BI: Extending Excel to Manipulate, Analyze, and Visualize Diverse Data. Serials Review45 (3): 184-188. https://doi.org/10.1080/00987913.2019.1644891.

3. Business intelligence using Power BI;De Groot;Business Innovation,2023

4. Emhana, S. 2018. Analysis of Non-Productive Time (NPT) in Drilling Operations - A case Study of the Ghadames Basin. Paper presented at the Second Scientific Conference of Oil and Gas, Ajdabiya, Libya, February.

5. Microsoft. 2023. About Power Query in Excel. https://support.microsoft.com/en-us/office/power-query-overview-and-learning-ed614c81-4b00-4291-bd3a-55d80767f81d.

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