Fayetteville Shale Drilling Optimization

Transcription

1 Case Study Fayetteville Shale Drilling Optimization Performance Drilling Advisor Service 1

2 Background Large Independent Operator drilling multiple wells in diverse areas with rigs of varying performance and experience. Operator makes business decision to start a drilling optimization program with the goals of reducing the drilling time, reducing bit runs, delivering wells more consistently and to improve the rig s performance, September Operator solicits information and bids from different drilling service companies about their drilling optimization services, October November Operator selects the NOV IMO Wellsite Performance Drilling Advisor (WPDA) service based on the service capabilities and completeness of the service to deliver the results required, December First deployment of WPDA service on 6 rigs, January

3 ,000 aces over 5 counties Fayetteville Shale lease area 35.6 Van Buren Co Cleburne Co. Latitude 35.4 White Co Conway Co. Faulkner Co. White Co Longitude 3

4 Drilling Optimization Definition of Service A drilling efficiency optimization service utilizing Real-Time Drilling Information that includes Data Quality Monitoring, Data Management, Drilling Efficiency Analysis, Customized Reporting and Dedicated Drilling Optimization Engineer Assistance. WPDA is the application of various tools, work flow processes, drilling techniques and expertise to optimize the drilling operations that will increase instantaneous ROP, minimize drilling costs, improve wellbore quality and safety. SPE

5 Data Hierarchy Drilling Optimization Planning Proactive Operation Event Recognition Reporting Data Gathering Wisdom Understanding Knowledge Information Data Doing the right things what is best Why How Who, What, Where, When Readings or Symbols 5

6 Drilling Optimization Service - Methodology o Engineering Analysis: o Analyze o Plan o Execute o Evaluate o Data Maintenance and Monitoring: o Availability o Quality o Delivery o 24/7 Real Time Technology Center: o Live streaming of 1 second data; surface and WITSML o Drilling Optimization Engineering support by Petroleum Engineers o Experienced drilling industry technical support professionals o Advance software and expertise for detailed analysis and optimization 6

7 Drilling Optimization Service Methodology, cont. o Rig Training and Support: o Focused training for rig personnel o Drilling optimization practices, drilling mechanics and drilling dynamics o Knowledge Management Practices: o Best practices across rig fleet and field o Quantitative engineering derived solutions o Relevant reporting for daily operations, section analysis and end of well o Continuous Improvement Methodology: o Evaluate, identify and classify dysfunctions o Prioritize bit and non-bit limiters o Redesign system to address the dysfunction or limiter o Execute, evaluate and repeat 7

8 Rig Site Topology Real Time Technology Center High-Resolution Data Collection and Aggregation -Surface -WITSML -MWD/LWD Data Monitoring & Management Drilling Optimization -Monitoring -Advising -Reporting Drilling Data Transmission Communications Remote Monitoring Remote Management -Doing more with less Streamline communications, situational awareness Operator s Office 8

9 Performance Analysis Cost Per Foot Average Drilling Hours Average Drill Days Average Total Depth 9

10 Performance Analysis Days Days Depth Depth

11 Economic Analysis o Average Savings of ~$135,000 + USD per well o Average bits saved range from 0 to 2 depending on area drilled o Average Cost per Metre Decrease of 25% o Average Drilling Hours Decrease by 39% o Average Days on Well Decrease by 29% o Average ROP Increase of 76% 11

12 Driller s Screen using Reference Data Streaming 12

13 Conclusions Drilling Optimization Services Conclusions: o Provide an economic benefit to the user. o Provide an operational benefit to the use. o Help achieve consistency across differing areas. o Provide a quantitative measurement of the drilling efficiency. o Provide a method to increase safety on the rig. o Minimize additional resources or infrastructure burdens be borne by the user. 13