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2.1), equation (2.31) becomes

      (2.34)images

      for 2-D geologic models, or

      (2.35)images

      for 1-D geologic models.

      Resistivity inversion methods have been implemented successfully for a variety of applications. However, the method has not been tested fully in various possible applications, such as for monitoring in-situ processes for improved oil recovery (IOR), environmental and geotechnical aspects of landfills and similar retainment structures. This may be because field surveys conducted until recently were done manually. Manual execution involves direct human activity to set up current and potential electrodes, electrode connections, and to take measurements of the induced potential field arising from current injection into the ground; this tends to make long-term investigations uneconomical or impractical. Another reason may be that field data are sometimes difficult to interpret in terms of a geologic model, owing to a lack of an appropriate interpretive tool (inversion model), poor resolution, poor quality data, or poor data coverage. The advent of the personal computer has led to dramatically increased efficiency in data collection. It is now possible to measure and interpret field data with a far better resolution and coverage than could be obtained with manual data collection, particularly if a fixed-electrode strategy is used. This in turn enhances the possibility of obtaining unambiguous geological interpretations of the field data because incomplete or varying locations for data sets over a time interval can be difficult to interpret. Mathematical tool discussed herein believes that the possible applications of direct-current resistivity methods are now limited mainly by our lack of imagination or opportunity, and it is likely that many more applications will be attempted in the future.

      Whenever a sufficient resistivity change over a region or at a front is generated as a result of a dynamic process such as groundwater contamination or IOR processes, the induced electrical-field response to that process can be modeled with an appropriate mathematical tool, and an optimum monitoring strategy determined. This monitoring capability can be achieved with currently available technology at relatively low expense, and it may be highly complementary to other monitoring methods (e.g., seismic response, geochemistry changes, surface displacement data, and pressure-volume-temperature (PVT) data in the case of IOR projects).

      In this article, applications of direct-current resistivity methods for monitoring in-situ processes are investigated and emphasized based on a solid mathematical basis. Attempt is made herein to explain the mathematical concept that can be used for monitoring in-situ processes (e.g., processes associated with geotechnical problems, processes of geo-environmental problems and processes of IOR projects involving water flooding and steam flooding).

      Referring to a mathematical equation (2.31), J(x, y, z) is a current density in the region of resistivity change after applying reciprocity between the receiver and transmitter. J’(x, y, z) may also be viewed mathematically as a Green’s function. The symbol τ in the above equation is the volume of an anomalous region where resistivity has been perturbed. Using equation (2.31), measurement sensitivity of the surface potential field to electrical resistivity changes can be expressed by the inner dot product of current densities in the anomalous zone to be monitored. This is mathematically a fundamental principle and concept that form the basis to introduce new techniques and strategies for resistivity measurements and tools for data interpretation. The physical insight derived from this analysis is that surface measurement sensitivity of the potential field is proportionally related to the amount of power dissipated (current density) around the zone of interest. This theoretical concept used in the derivation of equation (2.31) is commonly known as an adjoint solution or an adjoint state technique in the geophysical literature. This technique involves the transformation of the differential equation (in the case of resistivity, it describes the potential field due to a direct current point source) to yield a Green’s function. The Green’s function approach is quite common for implementing inversion of geophysical data. After deriving the theoretical formulation, an attempt has been made to interpret it physically. The physical insight derived from the relation has been used to guide sensitivity analyses as well as to introduce a new technique for resistivity measurements [3].

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