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Well integrity is one of the major concerns in long-term geologic storage sites due to its potential risk for well leakage and groundwater contamination. Evaluating changes in electrical responses due to energized steel-cased wells has the potential to quantify and predict possible wellbore failures as any kind of breakage or corrosion along highly-conductive well casings will have an impact on the distribution of subsurface electrical potential. However, realistic wellbore-geoelectrical models that can fully capture fine scale details of well completion design and state of well damage at the field scale require extensive computational effort or can even be intractable to simulate. To overcome this computational burden while still keeping the model realistic, we utilize the Hierarchical Finite Element Method which represents electrical conductivity at each dimensional component (1-D edges, 2-D planes and 3-D cells) of a tetrahedra mesh. This allows us to consider well completion designs with real-life geometric scales and well systems with realistic, detailed, progressive corrosion and damage in our models. Here, we present a comparison of possible discretization approaches of a multi-casing completion design in the finite element model. The impacts of the surface casing length and the coupling between concentric well casings, as well as the effects of the degree and the location of well damage on the electrical responses are also examined. Finally, we analyze real surface electric field data to detect the wellbore integrity failure associated with damage.
Well integrity is one of the major concerns in long-term geologic storage sites due to its potential risk for well leakage and groundwater contamination. Evaluating changes in electrical responses due to energized steel-cased wells has the potential to quantify and predict possible wellbore failures as any kind of breakage or corrosion along highly-conductive well casings will have an impact on the distribution of subsurface electrical potential. However, realistic wellbore-geoelectrical models that can fully capture fine scale details of well completion design and state of well damage at the field scale require extensive computational effort or can even be intractable to simulate. To overcome this computational burden while still keeping the model realistic, we utilize the Hierarchical Finite Element Method which represents electrical conductivity at each dimensional component (1-D edges, 2-D planes and 3-D cells) of a tetrahedra mesh. This allows us to consider well completion designs with real-life geometric scales and well systems with realistic, detailed, progressive corrosion and damage in our models. Here, we present a comparison of possible discretization approaches of a multi-casing completion design in the finite element model. The impacts of the surface casing length and the coupling between concentric well casings, as well as the effects of the degree and the location of well damage on the electrical responses are also examined. Finally, we analyze real surface electric field data to detect the wellbore integrity failure associated with damage.
Electromagnetic (EM) methods are among the original techniques for subsurface characterization in exploration geophysics because of their particular sensitivity to the earth electrical conductivity, a physical property of rocks distinct yet complementary to density, magnetization, and strength. However, this unique ability also makes them sensitive to metallic artifacts — infrastructure such as pipes, cables, and other forms of cultural clutter — the EM footprint of which often far exceeds their diminutive stature when compared to that of bulk rock itself. In the hunt for buried treasure or unexploded ordnance, this is an advantage; in the long-term monitoring of mature oil fields after decades of production, it is quite troublesome indeed. Here we consider the latter through the lens of an evolving energy industry landscape in which the traditional methods of EM characterization for the exploration geophysicist are applied toward emergent problems in well-casing integrity, carbon capture and storage, and overall situational awareness in the oil field. We introduce case studies from these exemplars, showing how signals from metallic artifacts can dominate those from the target itself and impose significant burdens on the requisite simulation complexity. We also show how recent advances in numerical methods mitigate the computational explosivity of infrastructure modeling, providing feasible and real-time analysis tools for the desktop geophysicist. Lastly, we demonstrate through comparison of field data and simulation results that incorporation of infrastructure into the analysis of such geophysical data is, in a growing number of cases, a requisite but now manageable step.
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