Numerical Simulation of Stress Change during Wellbore Injection

Abstract:

The important matter during any process in the well is wellbore integrity. Regarding to the geomechanics of the well, high bottom-hole pressure and low temperature could lead to the fracturing. The stress near the wellbore is a function of the flow and temperature, and it precisely determined to avoid the wellbore failure. The objective of this paper is to simulate stress change in the well for the injection. In order to analyze the stress in the wellbore a finite volume analysis has done for the wellbore. The stress equation relates to flow equation with the equation of principle stress. It means that the pressure is a key parameter for determination of the stress. The procedure which has to be followed is transforming the equations to weak form, meshing the defined shape and programing to obtain the values for each node. The result for the stress is obtained for some meshed bodies. The accuracy enhanced by choosing smaller mesh sizing.

• Periodical: Applied Mechanics and Materials (Volume 695)
• Pages: 688-693
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.695.688
• Online since: November 2014
• Authors: Mahmood Bataee*, Sonny Irawan
• Keywords: Finite Volume, Injection, Numerical Simulation, Stress State, Wellbore Studies

References

[1] Chin L. Y., L. K. Thomas, J. E. Sylte and R. G. Pierson: Iterative Coupled Analysis of Geomechanics and Fluid Flow for Rock Compaction in Reservoir Simulation, Oil & Gas Science and Technology, 57, (2002), Issue no. 5, 485-497.

DOI: 10.2516/ogst:2002032

[2] Du J., R. C. K. Wong: Development of a Coupled Geomechanics-Thermal Reservoir simulator Using Finite Element Method, Canadian International Petroleum Conference, Calgary, Alberta, (2005).

DOI: 10.2118/2005-027

[3] Espinoza, C.E., INTEVEP, S.A.: A New Formulation for Numerical Simulation of Compaction, Sensitivity Studies for Steam Injection, SPE Reservoir Simulation Symposium, San Francisco, California, (1983).

DOI: 10.2118/12246-ms

[4] Bataee, M., & Irawan, S. (2014). Review of Geomechanical Application in Reservoir Modeling. Journal of Applied Sciences, 14(10).

DOI: 10.3923/jas.2014.981.990

[5] M. Bataee, S. Irawan, (2014), The Effects of Geomechanics on the WAG Injection Model, Offshore Technology Conference-Asia, 25-28 March, Kuala Lumpur, Malaysia.

DOI: 10.2118/24706-ms

[6] Lewis R. W., C. E. Majorana, B. A. Schrefler.: A coupled finite element model for the consolidation of nonisothermal elastoplastic porous media, Journal of Transport in Porous Media, 1, (1986), Issue no. 2, 155-178.

DOI: 10.1007/bf00714690

[7] Lewis R. W., P. J. Roberts, B. A. Schrefler.: Finite element modelling of two-phase heat and fluid flow in deforming porous media, J. of Transport in Porous Media, 4, (1989), Issue no. 4, 319-334.

DOI: 10.1007/bf00165778

[8] Lewis R. W., B. A. Schrefler.: The finite element method in the static and dynamic deformation and consolidation of porous media, ISBN: 978-0-471-92809-6, 508 pages, (1998).

DOI: 10.1002/(sici)1099-1484(200001)5:1<85::aid-cfm94>3.0.co;2-8

[9] Pao W. K. S., R. W. Lewis, I. Masters.: A fully coupled hydro-thermo-poro-mechanical model for black oil reservoir simulation, International Journal for Numerical and Analytical Methods in Geomechanics, 25, (2001), Issue no. 12, 1229–1256.

DOI: 10.1002/nag.174

[10] Yin, S., M.B. Dusseault, and L. Rothenburg: Multiphase poroelastic modeling in semi-space for deformable reservoirs, Journal of Petroleum Science and Engineering, 64, (2009), 45-54.

DOI: 10.1016/j.petrol.2008.12.003

[11] Yin, S., M.B. Dusseault, and L. Rothenburg: Thermal reservoir modeling in petroleum geomechanics, International journal for numerical and analytical methods in geomechanics, 33, (2009), Issue no. 4, 449-485.

DOI: 10.1002/nag.723

[12] S. Mohseni, M. Bataee., (2011). Application of Artificial Intelligent Systems in ROP Optimization: a Case Study, SPE Middle East Unconventional Gas Conference and Exhibition, 31 January-2 February, Muscat, Oman.

DOI: 10.2118/140029-ms

[13] S. Edalatkhah, et al., (2010).

[14] M. Bataee, S. Irawan, (2014), Artificial Neural Network Model for Prediction of Drilling Rate of Penetration and Optimization of Parameters, Journal of the Japan Petroleum Institute 57(2), 65-70, 2014-03.

DOI: 10.1627/jpi.57.65

[15] Ali Ghalambor, et. al., (2010), Neural Networks in BHCP Prediction Performed Much Better Than Mechanistic Models, International Oil and Gas Conference and Exhibition in China, 8-10 June, Beijing, China.

DOI: 10.2118/130095-ms

[16] M. Bataee., M. Kamyab., (2010).

[17] M.R. Zare, et al., (2012), Production Optimization Using Different Scenarios of Gas Lift and ESP Installation,., World Applied Sciences Journal, 17 (4), 524-531.