Register      Login
The APPEA Journal The APPEA Journal Society
Journal of Australian Energy Producers
RESEARCH ARTICLE

Faster, higher, stronger: the competitive advantage of efficient data management for front-end decision making

Nathan Blundell
+ Author Affiliations
- Author Affiliations

Arrow Energy Pty Ltd, GPO Box 5262, Brisbane, Qld 4001, Australia. Email: Nathan.Blundell@arrowenergy.com.au

The APPEA Journal 57(1) 1-9 https://doi.org/10.1071/AJ16111
Accepted: 28 February 2017   Published: 29 May 2017

Abstract

With three major Australian coal seam gas (CSG) to liquefied natural gas export projects in operation phase, there is a need to identify new investment opportunities to maintain the required production and satisfy customer supply agreements. Considering the current global conditions of low commodity prices and the reduced availability of capital, both accuracy of data and efficient front-end decision making are essential. This paper proposes that well-defined front-end data processes and innovative data management technology can empower organisations to identify the value, and quantify the risks, of various development scenarios in a reduced time frame.

Arrow Energy’s combined Surat and Bowen gas projects contain thousands of CSG wells currently being considered for further development. This can require the generation of countless technical and commercial scenarios. The challenge was to reduce the turnaround time in running these scenarios and improve accuracy while providing seamless handover and traceability of data.

A new approach to data was required. By using global expertise in unconventional gas development projects, a data-centric development planning methodology was implemented. Industry best-practice geospatial tools were developed to introduce a new standard in well field layout scenarios, representing significant cost and schedule savings while improving risk identification and mitigation.

This paper outlines a shift from the traditional ‘disposable data’ mentality of front-end development to the creation of ‘live’ datasets that continuously mature to assess and develop CSG projects. It also identifies the significant advantages across the Australian oil and gas industry of implementing basic data management and using new technology to its full extent.

Keywords: coal seam gas (CSG), concept, data centric, data science, database, innovation, integration, project management, strategic decisions, unconventional gas.

Nathan Blundell has been managing projects in the Australian oil and gas industry for over 11 years in both the upstream and downstream sectors. He has been at Arrow Energy since 2010 as a project manager for upstream coal seam gas developments, including leading the gathering scope on the Bowen Gas Project Front End Engineering Design. More recently Nathan has worked as a development planner in the Front End Development team accountable for Arrow’s Surat Basin tenure. In his current role, Nathan is responsible for the development of technical and commercial scenarios to support front-end decision making. This role has given Nathan the opportunity to investigate innovative technology and data models to achieve maximum value for the business. Nathan’s previous experience working on upstream gathering projects highlighted the opportunity for efficiency and simplicity across the project lifecycle through the effective use of data. He also led the initial development of ‘gas factory’ processes at Arrow Energy, which required application and instructing of lean manufacturing theory.
Prior to Arrow, Nathan worked for BP at refineries in Australia and the US, filling a variety of roles in Projects, Maintenance and Operations. Refinery shutdowns exposed Nathan to the data management and structured processes needed to quickly enable informed decisions on complex projects. With experience executing challenging projects in both upstream and downstream sectors, Nathan has a great appreciation for reducing waste and realising the true value of projects. Born and raised on the Gold Coast, Nathan has a strong connection to Queensland and the efficient access and extraction of natural resources. This has led him to explore how best to identify opportunities for investment and provide an efficient (data-centric) approach to decision making. He is a chartered professional mechanical engineer (RPEQ) and holds a Bachelor of Mechanical Engineering (Hons).


References

Allison, N. (2016). More bang for your buck: optimising CSG extraction to achieve increased project value. The APPEA Journal 2016, 75–80.

Blundell, N. (2015). Breaking new ground: the hidden value of factory processes & data management. In ‘Proceedings of APGA Annual Convention and Exhibition’. 26–29 June 2015, Gold Coast, Qld, Australia. http://www.apga.org.au/knowledgebase/#21268 (accessed 20 March 2017).

Cheung, C.M., Goyal, P., Harris, G., Patri, O., Srivastava, A., Zhang, Y., Panangadan, A., Chelmis, C., McKee, R., Theron, M., Nemeth, T., and Prasanna, V.K. (2015). Rapid data integration and analysis for upstream oil and gas applications. In ‘Proceedings of SPE Annual Technical Conference and Exhibition’. 28–30 September 2015, Houston, TX, USA. https://www.onepetro.org/conference-paper/SPE-174907-MS (accessed 20 March 2017).

Courtney, H., Lovallo, D., and Clarke, C. (2013). Deciding how to decide. Harvard Business Review. , .

Fister Gale, S. (2011). Controlling chaos. PM Network 25, 26–31.

Gyara, S., Purwar, S., Bravo, C., and Queen, S. (2015). Managing the production lifecycle: a framework for scalable digital oilfield implementations. In ‘Proceedings of SPE Annual Technical Conference and Exhibition’. 28–30 September 2015, Houston, TX, USA. https://www.onepetro.org/conference-paper/SPE-174971-MS (accessed 20 March 2017).

Moran, A. (2015). ‘Managing Agile: Strategy, Implementation, Organisation and People.’ (Springer Verlag: Zurich.)

Popa, A.S., Grijalva, E., Cassidy, S., Medel, J., and Cover, A. (2015). Intelligent use of big data for heavy oil reservoir management. In ‘Proceedings of SPE Annual Technical Conference and Exhibition’. 28–30 September 2015, Houston, TX, USA. https://www.onepetro.org/conference-paper/SPE-174912-MS (accessed 20 March 2017)

Project Management Institute (PMI) (2013). ‘A Guide to the Project Management Body of Knowledge (PMBOK Guide)’. 5th edn. (Project Management Institute: Pennsylvania.)

Project Management Institute (PMI) (2014). What is project management? Available at https://www.pmi.org/about/learn-about-pmi/what-is-project-management (accessed 4 June 2014).

Puzey, M., and Latham, S. (2016). Enabling operational excellence through the effective management of master data. In ‘Proceedings of APPEA – Oil and Gas Conference and Exhibition 2016’. 5–8 June 2016, Brisbane, Qld, Australia. http://www.publish.csiro.au/AJ/AJ15081 (accessed 20 March 2017).

Randall, S.W. (2010). Managing risk and uncertainty provides competitive advantage. Oil and Gas Financial Journal 7, .

Redman, TC. (2015). 4 business models for the data age. Harvard Business Review. https://hbr.org/2015/05/4-business-models-for-the-data-age (accessed 4 March 2017).

Redman, TC. (2016). Bad data costs the U.S. $3 trillion per year. Harvard Business Review. https://hbr.org/2016/09/bad-data-costs-the-u-s-3-trillion-per-year (accessed 4 March 2017).

Rundle, R.T., Vuurboom, R., and Duroy, Y. (2015). End-to-end data provenance. In ‘Proceedings of SPE Annual Technical Conference and Exhibition’. 28–30 September 2015, Houston, TX, USA. https://www.onepetro.org/conference-paper/SPE-174803-MS (accessed 20 March 2017).

Schrage, M. (2016). How the big data explosion has changed decision making. Harvard Business Review , .

Shields, A., Mirhan, M., and Stratford, E. (2016). Maximising value by using good data to drive good decisions. The APPEA Journal 2016, 265–282.

Tadjeddine, K., and Lundqvist, M. (2016). ‘Policy in the Data Age: Data Enablement for the Common Good.’ (McKinsey, Paris.)

Taleb, N.N. (2007). ‘The Black Swan: The Impact of the Highly Improbable.’ (Random House: New York.)