Interpretation of deep directional resistivity measurements acquired in high-angle and horizontal wells using 3-D inversion
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This is a pre-copyedited, author-produced version of an article accepted for publication in Geophysical Journal International following peer review. The version of record Puzyrev, V. and Torres-Verdín, C. and Calo, V. 2018. Interpretation of deep directional resistivity measurements acquired in high-angle and horizontal wells using 3-D inversion. Geophysical Journal International. 213 (2): pp. 1135-1145 is available online at: https://academic.oup.com/gji/article/213/2/1135/4838989
The interpretation of resistivity measurements acquired in high-angle and horizontal wells is a critical technical problem in formation evaluation. We develop an efficient parallel 3-D inversion method to estimate the spatial distribution of electrical resistivity in the neighbourhood of a well from deep directional electromagnetic induction measurements. The methodology places no restriction on the spatial distribution of the electrical resistivity around arbitrary well trajectories. The fast forward modelling of triaxial induction measurements performed with multiple transmitter-receiver configurations employs a parallel direct solver. The inversion uses a pre-conditioned gradient-based method whose accuracy is improved using the Wolfe conditions to estimate optimal step lengths at each iteration. The large transmitter-receiver offsets, used in the latest generation of commercial directional resistivity tools, improve the depth of investigation to over 30 m from the wellbore. Several challenging synthetic examples confirmthe feasibility of the full 3-D inversion-based interpretations for these distances, hence enabling the integration of resistivity measurements with seismic amplitude data to improve the forecast of the petrophysical and fluid properties. Employing parallel direct solvers for the triaxial induction problems allows for large reductions in computational effort, thereby opening the possibility to invert multiposition 3-D data in practical CPU times.
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