Reducing Consumed Energy while Drilling an Oil Well through a Deep Rig Time Analysis
Rig time break down of more than 300 wells in one south west Iranian oil field has been analysed to determine effective parameters on non-productive time amount. Results show that the most common drilling problems always have been experienced by drilling engineers are Equipment failure, stuck pipe and lost circulation which expose huge expenses to the oil companies.
Several factors while drilling will govern how severe mud loss and stuck pipe would occur. These actually make analytical modelling of lost circulation or pipe sticking to somehow complicated. Hereby, employing artificial intelligence can be a leeway with proven capability and accuracy. In this research, operational parameters in Maroun oilfields are introduced to artificial neural networks to predict lost circulation severity, stuck pipe position and stuck pipe severity before happening. Results are well-matched with reality.
Key words: Energy; Drilling problems; Lost circulation; Stuck pipe; Rig time analysis
Adams, N. (1977). A field case study of differential-pressure pipe sticking: SPE 6716.
Al-Ajmi, A.M., & Zimmerman, R.W. (2006). Stability analysis of deviated boreholes using the mogi-coulomb failure criterion, With Applications to Some Oil and Gas Reservoirs: IADC/SPE 104035.
Biegler M.W., & Kuhn G.R. (1994). Advances in prediction of stuck pipe using multivariate statistical analysis: SPE 27529.
Dupriest, F.E (2005). Fracture closure stress (FCS) and lost returns practices: SPE 92192.
Howard, J.A., & Glover, S.B. (1994). Tracking stuck pipe probability while drilling: SPE 27528.
Moazzeni, A.R., Nabaei, M., Shahbazi, K. & Shadravan, A. (2010). Mechanical earth modeling improves drilling efficiency and reduces non-productive time (NPT): SPE 131718.
Moazzeni, A.R., Nabaei, M. & Ghadami, S. (2011). Decision making for reduction of non-productive time through an integrated lost circulation prediction. Journal of Petroleum Science and Technology, to be published.
Paes, P., Aragao, A., & Chen D.C. (2005). Cost effective drilling optimization technologies in Campos Basin: SPE 94785.
Pilehvari, A., and Nyshadham, V.R. (2002). Effect of material type and size distribution on performance of loss/seepage control material: SPE 73791.
Robert, J. B. (1995). Predicting production using a neural network: SPE 30202.
Runtuwene, M., Suprihono, S., Rizka, D., Prasetia, A. E., Toralde, J. S., & Nas S. (2009). Pressurized mud cap drilling drastically reduces non-productive time in soka field, south sumatera: SPE/IADC 125311.
Siruvuri. C., Nagarakanti. S. & Samuel R. (2006). Stuck pipe prediction and avoidance: a convolutional neural network approach: IADC/SPE 98378.
Weakley, R.R. (1990). Use of stuck pipe statistics to reduce the occurrence of stuck pipe: SPE 20410.
Wisnie, A.P., & Zheiwei, Z. (1994). Quantifying stuck pipe risk in gulf of mexico oil and gas drilling: SPE 28298.
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