The Influence of Data Quality on Workflows and Decision-Making in Well Delivery
- Steven J. Sawaryn (BP Exploration) | Nick Whiteley (BP Exploration) | Andrew Deady (BP Exploration) | Alexander Borresen (BP Exploration) | Nick Gibson (Kongsberg Intellifield)
- Document ID
- Society of Petroleum Engineers
- SPE Drilling & Completion
- Publication Date
- March 2011
- Document Type
- Journal Paper
- 32 - 40
- 2011. Society of Petroleum Engineers
- 2 Well Completion
- Smart Agents, Decision Making, Workflows, WITSML, Data Quality
- 4 in the last 30 days
- 754 since 2007
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The paper discusses how data quality influences workflows and decision making in drilling and completions and examines the use of semiautomated processes for quality assurance. With poor data, additional steps are required and workflows must be repeated. In even relatively simple situations, controlled tests suggest that small changes or omissions may have a significant influence on the work efficiency or outcome.
In earlier work, the quality of any data stream has been described in terms of identity, presence, measurement frequency, accuracy, continuity, units, and associated metadata. For some of these, a degree of self-checking is possible, applying simple algorithms to the data stream to detect presence and bounds, with alarms to alert the operator if these are transgressed. In other cases, such as the change in drag and torque with depth, the stream must be checked against a trend, called a pseudolog, determined from the physics. These calculations are performed by "smart agents" directly in real time on the wellsite information transfer standard markup language (WITSML) data feed from the rig. The paper describes the early work in developing smart agents to address data quality and structure of the associated tool kit that can be used to construct more-complex agents from a wider selection of data sources, including system-generated ones. The computational resources required are also discussed.
The increase in digital data and skills shortage makes manual assurance of all the data streams neither practical nor cost effective. Because current applications are not tolerant of errors and omissions, a step change in data quality is needed if more-automated workflows are to be achieved. Greater assurance of the data at source and an improved understanding of the workflows will help.
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Ali, T.H., Sas, M., Hood, J.A., Lemke, S.R., Srinivasan, A., McKay, J.,Fereday, K.S. et al. 2008. HighSpeed Telemetry Drill Pipe Network Optimizes Drilling Dynamics and WellborePlacement. Paper SPE 112636 presented at the IADC/SPE Drilling Conference,Orlando, Florida, USA, 4-6 March. doi: 10.2118/112636-MS.
Bayerl, P.S., Lauche, K., Crichton, M., Sawaryn, S.J., and Deady, A. 2009.Exercises in Distributed TacticalDecision-Making in Advanced Collaborative Environments. Paper SPE 123101presented at the SPE Digital Energy Conference and Exhibition, Houston, 7-8April. doi: 10.2118/123101-MS.
Cayeux, E., Dvergsnes, E.W., and Iversen, F. 2009. Real-Time Optimization of theDrilling Process--Challenges in Industrialization. Paper SPE 119650presented at the SPE/IADC Drilling Conference and Exhibition, Amsterdam, 17-19March. doi: 10.2118/119650-MS.
Energistics. 2010. WITSML Standards, http://www.energistics.org/witsml-standard.
Hite, J.R., Crawley, C., Deaton, D.F., Farid, K., and Sternevsky, M. 2007.Barriers to Implementation ofReal-Time Operations Technology. Paper SPE 110236 presented at the SPEAnnual Technical Conference and Exhibition, Anaheim, California, USA, 11-14November. doi: 10.2118/110236-MS.
Hurst, A., Tischler, G., and Arkalgud, R. 2009. Predicting Reservoir CharacteristicsFrom Drilling and Hydrocarbon-Gas Data Using Advanced ComputationalMathematics. Paper SPE 123785 presented at Offshore Europe, Aberdeen, 8-11September. doi: 10.2118/123785-MS.
Kårtveit, S., Sawaryn, S.J., Jones, B.L., Wahlen, M., and Mosness, T.L.2003. Organisational and TechnicalAspects of an Ultra-Reliable Mud-Logging Service Capable of Remote Operationand Control. Paper SPE 84168 presented at the SPE Annual TechnicalConference and Exhibition, Denver, 5-8 October. doi: 10.2118/84168-MS.
Klayman, J. and Ha, Y.-W. 1987. Confirmation,disconfirmation, and information in hypothesis testing. PsychologicalReview 94 (2): 211-228. doi:10.1037/0033-295X.94.2.211.
Kyllingstad, A., Horpestad, J.L., Klakegg, S., Kristiansen, A., and Aadnoey,B.S. 1993. Factors Limiting theQuantitative Use of Mud-Logging Data. Paper SPE 25319 presented at the SPEAsia Pacific Oil and Gas Conference, Singapore, 8-10 February. doi:10.2118/25319-MS.
Landre, E., Ølmheim, J., Waersland, G.O., and Rønneberg, H. 2006. Software Agents--An EmergentSoftware Technology That Enables Us to Build More Dynamic, Adaptable, andRobust Systems. Paper SPE 103354 presented at the SPE Annual TechnicalConference and Exhibition, San Antonio, Texas, USA, 24-27 September. doi:10.2118/103354-MS.
Laughlin, P.R., Magley, V.J., and Shupe, E.I. 1997. Positive and NegativeHypothesis Testing by Cooperative Groups. Organizational Behavior andHuman Decision Processes 69 (3): 265-275.doi:10.1006/obhd.1997.2687.
Lynn, P.A. 1992. Digital Signals: Processors and Noise. Hampshire,UK: Palgrave Macmillan.
Pickering, J.G., Kreijer, J., Grovik, L.O., Franssens, D., Deeks, N.R.,Doniger, A., and Schey, J. 2009a. WITSML "Comes of Age" for the GlobalDrilling and Completions Industry. Paper SPE 124347 presented at the SPEAnnual Technical Conference and Exhibition, New Orleans, 4-7 October. doi:10.2118/124347-MS.
Pickering, J.G., Whiteley, N., Rochford, J., Sheil, K., and Lowe, J. 2009b.WITSML Real TimeInter-operability Testing. Paper SPE 123208 presented at the SPE DigitalEnergy Conference and Exhibition, Houston, 7-8 April. doi:10.2118/123208-MS.
Sawaryn, S.J., Deady, A., Whiteley, N., Critchley, C., Brown, L., andGibson, N. 2009a. Getting Data toDrilling and Completions Teams and Vice Versa. Paper SPE 123174 presentedat the SPE Digital Energy Conference and Exhibition, Houston, 7-8 April. doi:10.2118/123174-MS.
Sawaryn, S.J., Goodwin, S., Deady, A., Critchley, C., and Swanson, B. 2009b.The Implementation of a Drilling& Completions Advanced Collaborative Environment--Taking Advantage ofChange. Paper SPE 123801 presented at Offshore Europe, Aberdeen, 8-11September. doi: 10.2118/123801-MS.
Smith, S.W. 1997. The Scientist and Engineer's Guide to Digital SignalProcessing. San Diego, California: California Technical Publishing.
Vindasius, J. 2008. TheIntegrated Collaboration Environment as a Platform for New Ways of Working:Lesson Learned From Recent Projects. Paper SPE 112218 presented at theIntelligent Energy Conference and Exhibition, Amsterdam, 25-27 February. doi:10.2118/112218-MS.
Womer, K.A. 2004. Use of 21st Century Computer and CommunicationsTechnologies to Make Effective Drilling Decisions. Presentation 101516 given asan SPE Distinguished Lecture during the 2003-2004 season.