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The Future of Surveillance--A Survey of Proven Business Practices for Use in Oil and Gas
- Mark Lochmann (Halliburton)
- Document ID
- Society of Petroleum Engineers
- SPE Economics & Management
- Publication Date
- October 2012
- Document Type
- Journal Paper
- 235 - 247
- 2012. Society of Petroleum Engineers
- 7.6.6 Artificial Intelligence
- 2 in the last 30 days
- 622 since 2007
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Surveillance in one form or another has been used in oil and gas production almost since the industry began. The initial goal was relatively simple and straightforward: monitoring output against production targets for individual wells and troubleshooting those same wells when problems occurred. The actual scope of what could be accomplished was limited by available resources and lack of tools and technology, so only a very few high-value wells could be monitored closely.
With modern complex oil- and gas-production operations, the goal of surveillance has evolved from ensuring a single well's performance to managing a producing asset against its potential--a much loftier endeavor that must consider each of the system components, the interaction of those components, and the impact of factors external to the system. Traditional approaches to surveillance are no longer adequate to meet the current and continuously emerging and increasingly complex requirements of oil and gas operations. Modern and next-generation surveillance systems must deliver more.
More recently, in both mature fields and green fields, the industry has seen increased implementation of more-sophisticated solutions with richer capabilities (e.g., monitoring centers that feed data into real-time displays; the enabling of operations staff to see the status of all key measurements; and model-based, integrated workflows to automate and facilitate operational excellence). The addition of advanced analytics, expert systems, and process automation (all of which routinely leverage real-time information) has taken surveillance from gathering production data on grease books to sophisticated solutions that combine business or operational intelligence with automated technical calculations. Indeed, these are the types of surveillance solutions expected by forward thinking managers. However, despite these successes, widespread uptake of these types of solutions is slow, as is often the case in our industry.
This paper provides a survey of business practices proven in other complex industries, including management by exception (MBE), business intelligence (BI), situational awareness (SA), model-based decision support (MBDS), advanced process control (APC), and consequential analysis (CA). With learning from use in other industries, these business practices, enabled by state-of the art information technology, can be combined and implemented to build next-generation surveillance solutions that will allow oil and gas producers to manage production assets against their potential in a safe, environmentally responsible way and in support of corporate goals.
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