Bayesian inversion for rapid multiwell interpretation of well logs and core data: Applications to unconventional organic-shale formations

Author:

Deng Tianqi1ORCID,Ambía Joaquín1,Torres-Verdín Carlos2

Affiliation:

1. The University of Texas at Austin, Department of Petroleum and Geosystems Engineering, Austin, Texas, USA.

2. The University of Texas at Austin, Department of Petroleum and Geosystems Engineering, Austin, Texas, USA. (corresponding author)

Abstract

Multimineral analysis is widely used to calculate in situ porosity, fluid saturation, and mineralogy of rocks penetrated by a well. It delivers weight/volumetric concentrations of rock solid/fluid constituents by combining multiple borehole geophysical measurements and often is referred to as petrophysical joint inversion. Recently, a probabilistic method was developed for improved petrophysical estimation of rock constituents and their uncertainty from well logs. This method mitigates borehole and instrument-related environmental effects present in the measurements and efficiently propagates the uncertainty from measurement noise and rock-physics models (RPMs) to compositional/petrophysical estimations. The probabilistic estimation method is extended to the challenging conditions of multiple neighboring wells penetrating similar rock formations where borehole/drilling environmental conditions, borehole instruments, and measurement noise may vary from well to well. A calibration step is performed in a few key wells with core data and/or advanced borehole measurements; it enables the same RPMs and prior models to be implemented in nearby wells but with limited measurements. In addition, a precomputed surrogate model constructed with radial basis function interpolation is implemented for accurate and efficient nuclear-property calculations. The multiwell interpretation method is verified using synthetic and field examples of organic-rich shale formations. Results find that the probabilistic method (1) improves rock petrophysical/compositional estimations by mitigating borehole environmental effects and incorporating a priori knowledge, (2) yields regionally consistent compositions among wells, and (3) quantifies the uncertainty of the estimations. As a result, the probabilistic approach is especially suitable for assessing petrophysical/compositional properties in multiwell settings with complex rock constituents and/or limited borehole measurements.

Funder

The University of Texas at Austin's Research Consortium on Formation Evaluation

Brian James Jennings Memorial Endowed Chair in Petroleum and Geosystems Engineering, The University of Texas at Austin

Publisher

Society of Exploration Geophysicists

Subject

Geochemistry and Petrology,Geophysics

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