Loss Circulation Prevention during Drilling Operation - Risk Analysis Approach and its Implications

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Drilling engineers and operators are stuck with challenges associated with loss circulation of drilling fluids in wellbores during drilling operation. At such times, a clear and careful decision is required in order to minimize cost or save resources that would have been lost in the bid to remedy the situation. This then informs the need to deploy reliable tools that will inform useful decisions as drawn from a thorough risk-analysis coined from the information gathered from the formation characteristics and operating pressure. In this study, a real-time statistic based approach was adopted in carrying out risk-evaluation of loss circulation events in a wellbore. Based on the expected opportunity loss analysis, it is often non-negotiable to consider other options when the analytical solution suggests that the well should be “abandoned”. For the decision tree, at the decision node, D1, the expected loss of the seal off zone option is $161.25, the expected loss of the drill ahead option is $19.2 and the expected loss of the abandon option is $13.2. Since the expected loss of the abandon option is less than the expected value of both the seal off and the drill ahead option, it is recommended to abandon the well. Furthermore, the risk analysis proved to be a veritable tool considering the cost implications of other options; and can also serve as basis for automated decision-making.

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102-109

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February 2020

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© 2020 Trans Tech Publications Ltd. All Rights Reserved

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[1] D. Whitfill, H. Wang, Making Economic Decisions to Mitigate Lost Circulation, In: proceedings of SPE Annual Technical Conference and Exhibition, Dallas, Texas, USA, 9–12 October 2005. 10.2118/95561-MS.

Google Scholar

[2] E.E. Okoro, A. Dosunmu and S. Iyuke, Data on Cost analysis of drilling mud displacement during drilling operation, Data in Brief, 19 (2018)535-541. https://doi.org/10.1016/j.dib.2018.05.075.

DOI: 10.1016/j.dib.2018.05.075

Google Scholar

[3] N. Bilim, A. Çelik and B. Kekeç, A study in cost analysis of aggregate production as depending on drilling and blasting design, Journal of African Earth Sciences 134 (2017) 564-572.

DOI: 10.1016/j.jafrearsci.2017.07.024

Google Scholar

[4] M.A. Mian, Project Economics and Decision Analysis, Tulsa Oklahoma, Pennwell Corporation, (2011).

Google Scholar

[5] H.H. Alkinani, A.T.T. Al-Hameedi, S. Dunn-Norman, R.E. Flori, M.T. Alsaba, A.S. Amer and S.A. Hilgedick, Using data mining to stop or mitigate lost circulation, Journal of Petroleum Science and Engineering 173(2019) 1097-1108.

DOI: 10.1016/j.petrol.2018.10.078

Google Scholar

[6] K.C. Igwilo, E.E. Okoro, O. Agwu, C. Onedibe, S.I. Ibeneme and N.O. Okoli, Experimental Analysis of Persea americana as Filtration Loss Control Additive for Non-Aqueous Drilling Fluid, International Journal of Engineering Research in Africa, Vol. 44, pp.8-21.

DOI: 10.4028/www.scientific.net/jera.44.8

Google Scholar

[7] E.E. Okoro, A. Dosunmu, B. Oriji and S. Iyuke, Impact of Reversible Invert Emulsion Drilling Fluid rheology on productivity, SPE-178308-MS, In: proceedings of Nigerian Annual Technical Conference and Exhibition, (2015).

DOI: 10.2118/178308-ms

Google Scholar

[8] M. Sabah, M. Talebkeikhah, F. Agin, F. Talebkeikhah and E. Hasheminasab, Application of decision tree, artificial neural networks, and adaptive neurofuzzy inference system on predicting lost circulation: A case study from Marun oil field, Journal of Petroleum Science and Engineering 177 (2019) 236–249.

DOI: 10.1016/j.petrol.2019.02.045

Google Scholar

[9] C. Xu, Y. Kang, F. Chen and Z. You, Fracture plugging optimization for drill-in fluid loss control and formation damage prevention in fractured tight reservoir, Journal of Natural Gas Science and Engineering 35(2016) 1216-1227.

DOI: 10.1016/j.jngse.2016.09.059

Google Scholar

[10] E.E. Okoro, K.C. Igwilo, K. Ifeka, I.S. Okafor and I. Sangotade, Cellulosic Cyperus esculentus L. as a filtrate loss modifier in field applicable aqueous and non-aqueous drilling fluids, Journal of Petroleum Exploration and Production Technology, 9(2019) 1331-1337. https://doi.org/10.1007/s13202-018-0580-y.

DOI: 10.1007/s13202-018-0580-y

Google Scholar

[11] S. Salehi and R. Nygaard, Numerical modeling of induced fracture propagation: a novel approach for lost circulation materials (LCM) design in borehole strengthening applications of deep offshore drilling, In: SPE 135155, SPE Annual Technical Conference and Exhibition, San Antonio, USA, 8-10 October, (2012).

DOI: 10.2118/135155-ms

Google Scholar

[12] J. Cook, F.G. Cock, Q. Guo, M. Hodder and E. Van Oort, Stabilizing the Wellbore to Prevent Lost Circulation, Oil Field Review, Schlumberger, (2012).

Google Scholar

[13] B. Rehm, J. Schubert, A. Haghshenas, A.S. Parknejad and J. Hughes, Manage Pressure Drilling. Gulf Publishing Company, Houston, Texas, (2008).

Google Scholar

[14] E.E. Okoro, A.A. Zuokumor, I.S. Okafor, K.C. Igwilo and K.B. Orodu, Determining the optimum concentration of multiwalled carbon nanotubes as filtrate loss additive in field‑applicable mud systems, Journal of Petroleum Exploration and Production Technology, 2019. https://doi.org/10.1007/s13202-019-0740-8.

DOI: 10.1007/s13202-019-0740-8

Google Scholar

[15] H.H. Alkinani, A.T.T. Al-Hameedi, S. Dunn-Norman, R.E. Flori, M.T. Alsaba, A.S. Amer and S.A. Hilgedick, Using data mining to stop or mitigate lost circulation, Journal of Petroleum Science and Engineering 173(2019) 1097-1108.

DOI: 10.1016/j.petrol.2018.10.078

Google Scholar

[16] A.K. Abbas, A.A. Bashikh, H. Abbas and H.Q. Mohammed, Intelligent decisions to stop or mitigate lost circulation based on machine learning, Energy 183(2019) 1104-1113.

DOI: 10.1016/j.energy.2019.07.020

Google Scholar

[17] R. Gholami, A. Moradzadeh, V. Rasouli and J. Hanachi, Practical application of failure criteria in determining safe mud weight windows in drilling operations, J Rock Mechanics Geotech Eng 2014;6(1):13e25. https://doi.org/10.1016/j.jrmge. 2013.11.002.

DOI: 10.1016/j.jrmge.2013.11.002

Google Scholar

[18] Z. Genga, H. Wang, M. Fan, Y. Lu, Z. Nie, Y. Ding and M. Chen, Predicting seismic-based risk of lost circulation using machine learning, Journal of Petroleum Science and Engineering 176 (2019) 679–688.

DOI: 10.1016/j.petrol.2019.01.089

Google Scholar

[19] P. Behnoud Far and p. Hosseini, Estimation of lost circulation amount occurs duringunder balanced drilling using drilling data andneural network, Egyptian Journal of Petroleum, 26(2017) 627-634.

DOI: 10.1016/j.ejpe.2016.09.004

Google Scholar

[20] Z. You, P. Bedrikovetsky, A. Badalyan and M. Hand, Particle mobilization in porous media: temperature effects on competing electrostatic and drag forces, Geophys. Res. Lett. 42 (2015) 2852-2860.

DOI: 10.1002/2015gl063986

Google Scholar

[21] A. Nasiri, A. Ghaffarkhah, M.K. Moraveji, A. Gharbanian and M. Valizadeh, Experimental and field test analysis of different loss control materials for combating lost circulation in bentonite mud, J. Nat. Gas Sci. Eng. 44 (2017) 1–8.

DOI: 10.1016/j.jngse.2017.04.004

Google Scholar

[22] A.T.T. Al-Hameedi, H.H. Alkinani, S. Dunn-Norman, R.E. Flori and S.A. Hilgedick, Real-time lost circulation estimation and mitigation, Egyptian Journal of Petroleum 27(2018) 1227–1234.

DOI: 10.1016/j.ejpe.2018.05.006

Google Scholar

[23] Y. Chang, X. Wu, G. Chen, J. Ye, B. Chen, L. Xu, J. Zhou, Z. Yin and K. Ren, Comprehensive risk assessment of deepwater drilling riser using fuzzy Petri net model, Process Safety and Environmental Protection 117(2018) 483-497.

DOI: 10.1016/j.psep.2018.05.021

Google Scholar

[24] M.Z. Lukawski, B.J. Anderson, C. Augustine, L.E. Capuano Jr., K.F. Beckers, B. Livesay and J.W. Tester, Cost analysis of oil, gas, and geothermal well drilling, Journal of Petroleum Science and Engineering 118(014) 1–14.

DOI: 10.1016/j.petrol.2014.03.012

Google Scholar

[25] L. Zhang, S. Wu, W. Zheng and J. Fan, A dynamic and quantitative risk assessment method with uncertainties for offshore managed pressure drilling phases, Safety Science 104(2018) 39–54.

DOI: 10.1016/j.ssci.2017.12.033

Google Scholar

[26] P. Amir-Heidari, R. Maknoon, B. Taheri and M. Bazyari, Identification of strategies to reduce accidents and losses in drilling industry by comprehensive HSE risk assessmentdA case study in Iranian drilling industry, Journal of Loss Prevention in the Process Industries 44(2016) 405-413.

DOI: 10.1016/j.jlp.2016.09.015

Google Scholar

[27] K. Yost, A. Valentin and H.H. Einstein, Estimating cost and time of wellbore drilling for Engineered Geothermal Systems (EGS) – Considering uncertainties, Geothermics 53(2015) 85-99.

DOI: 10.1016/j.geothermics.2014.04.005

Google Scholar

[28] Z.Y. Sun, J.L. Zhou and L.F. Gan, Safety assessment in oil drilling work system based on empirical study and Analytic Network Process, Safety Science 105(2018) 86–97.

DOI: 10.1016/j.ssci.2018.02.004

Google Scholar

[29] M.A. Mian, Project Economics and Decision Analysis. Tulsa Oklahoma : Pennwell Corporation, (2011).

Google Scholar

[30] A. Lavrov, Lost Circulation: Mechanisms and Solutions, Gulf Professional Publishing, (2016).

Google Scholar