New Software for Processing of LWD Extradeep Resistivity and Azimuthal Resistivity Data
- Mikhail Vladimirovich Sviridov (Baker Hughes) | Anton Mosin (Baker Hughes) | Yuriy Antonov (Baker Hughes) | Marina Nikitenko (Baker Hughes) | Sergey Martakov (Baker Hughes) | Michael Rabinovich (BP)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- May 2014
- Document Type
- Journal Paper
- 109 - 127
- 2014.Society of Petroleum Engineers
- 1.6.9 Coring, Fishing, 5.6.1 Open hole/cased hole log analysis, 1.12.2 Logging While Drilling, 1.6 Drilling Operations, 1.6.7 Geosteering / Reservoir Navigation
- inversion of resistivity data, logging while drilling, geosteering, azimuthal resistivity tool, extradeep resistivity tool
- 2 in the last 30 days
- 663 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 5.00|
|SPE Non-Member Price:||USD 35.00|
In petroleum exploration, reservoir navigation is used for reaching a productive reservoir and placing the borehole optimally inside the reservoir to maximize production. For proper well placement, it is necessary to calculate in real-time the parameters of the formation we are drilling in and the parameters of formations we are approaching. On the basis of these results, a decision to change the direction of drilling could be made. Modern logging-while drilling (LWD) extra-deep and azimuthal resistivity tools acquire multicomponent, multispacing, and multifrequency data that provide sufficient information for resolving the surrounding formation parameters. These tools are generally used for reservoir navigation and real-time formation evaluation. However, real time interpretation software is very often based on simplified resistivity models that can be inadequate and lead to incorrect geosteering decisions. The core of the newly developed software is an inversion algorithm based on transversely isotropic layered Earth with an arbitrary number of layers. The following model parameters are determined in real time: horizontal and vertical resistivities and thickness of each layer, formation dip, and azimuth. The inversion algorithm is based on the method of the most-probable parameter combination. The algorithm has good performance and excellent convergence because of its enhanced capability of avoiding local minima. This capability enables interpretation of real-time resistivity data, including azimuthal and extra-deep measurements. A graphical user interface (GUI) was developed to provide an interactive environment for each stage of the resistivity data interpretation process: preview of input resistivity logs, initial preprocessing and filtering of raw data, creation of initial guess, running inversion and viewing inversion results, and quality-control indicators. Applications of the developed software will be shown on a series of synthetic examples and field data from the North Sea and Gulf of Mexico (GOM). This newly developed software is currently in use for real-time reservoir navigation and post-well analysis.
|File Size||3 MB||Number of Pages||19|
Dennis, J. E. and Schnabel, R. B. 1988. Numerical Methods for Unconstrained Optimization and Nonlinear Equations. Moscow, USSR: Mir Publishers.
Fang, S., Merchant, A., Hart, E., et al. 2008. Determination of Structural Dip and Azimuth from LWD Azimuthal Propagation Resistivity Measurements in Anisotropic Formations. Paper SPE 116123 presented at 2008 SPE Annual Technical Conference and Exhibition, Denver, Colorado, 21–24 September. http://dx.doi.org/10.2118/116123-MS.
Gill, P. E. and Murrey, W. 1977. Numerical Methods for Constrained Optimization. Moscow, USSR: Mir Publishers.
Helgesen, T. B., Meyer, W. H., Thorsen, A. K., et al. 2004. Accurate Wellbore Placement Using a Novel Extra Deep-Resistivity Service. Paper SPE 94378 presented at the SPE Europec/EAGE Annual Conference, Madrid, Spain, 13–16 June. http://dx.doi.org/10.2118/94378-MS.
Himmelblau, D. 1975. Applied Nonlinear Programming. Moscow, USSR: Mir Publishers.
Moré, J. J and Sorensen, D. C. 1983. Computing a Trust Region Step. SIAM J. Sci. Stat. Comp. 4 (3): 553–572. http://dx.doi.org/10.1137/0904038.
Pardalos, P. M. and Romeijn, H. F. 2002. Handbook of Global Optimization, Vol. 2. Dordrecht, Netherlands: Kluwer.
Pustilnik, E. I. 1968. Statistical Methods of Data Analyze and Processing. Moscow, USSR: Nauka.
Rabinovich, M., Le, F., Lofts, J., et al. 2011. The Vagaries and Myths of Look-Around Deep-Resistivity Measurements While Drilling. Oral presentation given at the Society of Petrophysicists and Well Log Analysts (SPWLA) 52nd Annual Logging Symposium, Colorado Springs, Colorado, 14–18 May.
Seydoux, J., Tabanou, J., Ortenzi, L., et al. 2003. A Deep-Resistivity Logging-While-Drilling Device for Proactive Geosteering. Paper OTC 15126 presented at the Offshore Technology Conference, Houston, Texas, 5–8 May. http://dx.doi.org/10.4043/15126-MS.
Stone, M. 1974. Cross-Validatory Choice and Assessment of Statistical Predictions. J. Roy. Stat. Soc. B. Met. 36 (2): 111–147. http://www.jstor.org/stable/2984809.
Tikhonov, A. N. and Arsenin, V. J. 1979. Methods of Solving Ill-Posed Problems. Moscow, USSR: Nauka.
Verlan, A. F. and Sizikov, V. S. 1986. Integral Equations: Methods, Algorithms, Codes. Kiev, USSR: Naukova Dumka.
Wang, T., Chemali, R., Hart, E., et al. 2007. Real-Time Formation Imaging, Dip, And Azimuth While Drilling From Compensated Deep Directional Resistivity. Paper SPWLA 2007_NNN presented at the 48th SPWLA Annual Logging Symposium, Austin, Texas, 3–6 June.
Yanovskaya, T. B. and Porokhova, L. N. 1983. Inverse Problems in Geophysics. Leningrad, USSR: Leningrad State University Press.