Remote reservoir resistivity mapping

Details Remote reservoir resistivity mapping Remote reservoir resistivity mapping

2000-09-06

2003-08-05

Snow, Walter E. (Department: 2862)

Electricity: measuring and testing

Of geophysical surface or subsurface in situ

Using electrode arrays, circuits, structure, or supports

C324S359000, C702S005000

Reexamination Certificate

active

06603313

ABSTRACT:

FIELD OF THE INVENTION
This invention relates generally to the field of geophysical prospecting. More particularly, the invention relates to surface measurement of subsurface geologic formation electrical resistivity. Specifically, the invention is a method of combining seismic and electromagnetic data to prospect for subsurface formations that contain hydrocarbons.
BACKGROUND OF THE INVENTION
Remote mapping and analysis from the surface of the earth of hydrocarbons reservoired at depth remains a difficult technical task. This is so despite recent advances in 3D seismic imaging, seismic direct hydrocarbon indicator (DHI) and amplitude variation with offset (AVO) analyses, and seismic attribute mapping and interpretation. Seismic detection difficulties arise in part from the fact that the mechanical properties of reservoirs, to which the seismic probe responds, are often only slightly modified when hydrocarbons replace formation waters, especially in the case of oil. The modification may be of the order of only 10's of percent. Subtle mechanical effects related to seismic wave propagation and reflection can mask DHI and AVO signatures or even produce misleading signatures. For example, low gas saturation in water sands can produce false seismic DHIs. Because of such effects, drill-well success rates are too low and exploration costs are too high in many basins. In addition, rapid and low-cost assessment of discovered undeveloped hydrocarbon reserves requires good knowledge of reservoir properties at large distances from the discovery well. Acquiring this knowledge is problematic using only seismic data. There is an urgent need to remotely measure and map other reservoir formation properties that are sensitive to hydrocarbons, and to combine interpretation of these other properties with interpretations of seismic data and their mapped attributes. One particularly important formation property is electrical resistivity, which is strongly related to the pore fluid type and saturation.
The bulk electrical resistivity of reservoirs is often increased substantially when hydrocarbons are present. The increase can be of the order of 100's to 1000's of percent. However, increased formation resistivity alone may not uniquely indicate hydrocarbons. For instance, carbonates, volcanics, and coals can also be highly resistive. Nevertheless, spatial correlation of high formation resistivity with potential traps imaged by seismic data, or with seismic DHI or AVO effects at reservoir depth, provides strong evidence of the presence of oil or gas and valuable information on their concentrations. For example, a low gas saturation high-porosity sandstone reservoir encased in shale can produce a strong seismic DHI and an AVO curve indicative of gas. However, it would also have low electrical resistivity and hence would be a high-risk drill-well prospect.
Most hydrocarbon reservoirs are inter-bedded with shale stringers or other non-permeable intervals and hence are electrically anisotropic at the macroscopic scale. Thus, it is important to measure both the vertical (transverse) and horizontal (longitudinal) electrical resistivities of the reservoir interval. Remote measurement of the vertical and horizontal resistivities of the reservoir interval, combined with estimation of the resistivity of the non-permeable bedding, would provide quantitative bounds on the reservoir's fluid content, such as the hydrocarbon pore volume. However, there is no existing technology for remotely measuring reservoir formation resistivity from the land surface or the seafloor at the vertical resolution required in hydrocarbon exploration and production. Based on the thicknesses of known reservoirs and predicted future needs, this required resolution would be equal to or less than two percent of depth from the earth's surface or seafloor. For example, this would resolve a 200-ft net reservoir thickness (vertical sum of hydrocarbon bearing rock thicknesses within the reservoir interval) or less at a typical 10,000-ft reservoir depth.
Overviews of electromagnetic imaging technology are given by M. N. Nabighian (ed.),
Electromagnetic Methods in Applied Geophysics
, Vols. 1 & 2, SEG Investigations in Geophysics No. 3, 1988; A. G. Nekut and B. R. Spies,
Proceedings IEEE
, v. 77, 338-362, 1989; and by M. S. Zhdanov and G. V. Keller,
The Geoelectrical Methods in Geophysical Exploration
, Elsevier, 1994. Imaging of electrically conductive objects such as ore bodies has been the dominant application for electromagnetic methods. In applications for hydrocarbon exploration, most of the technology was developed to image large geological structures in regions where seismic data are low in quality or are absent, and little other geological or geophysical information is available.
Direct exploration for hydrocarbons using surface-based electromagnetic imaging has been attempted since the 1930s, but with little commercial success. This lack of success is due to the low spatial resolution and the ambiguous interpretation results of current electromagnetic methods, when applied in stand-alone and spatially under-sampled ways to the geological imaging problem. Low subsurface resolution is one consequence of the diffusive nature of the low frequency electromagnetic waves, that is, below 1 kHz, required to penetrate the earth to reservoir depths. The vertical resolution of such electromagnetic waves is relatively insensitive to bandwidth, unlike the seismic case, but is very sensitive to the accuracy and precision of phase and amplitude measurements and to the inclusion of constraints from other data. That is, the unconstrained geophysical electromagnetic data inverse problem is mathematically ill posed, with many possible geologic structures fitting electromagnetic data equally well. Consequently, the vertical resolution of unconstrained electromagnetic imaging is typically no better than 10 percent of depth. This gives a resolution of only a 1000-ft net reservoir thickness at a typical 10,000-ft reservoir depth. However, within a given resolved layer, conventional resistivity measurement accuracy can be within a factor of two, which is adequate for oil and gas exploration.
Electromagnetic technology that is applicable to direct reservoir imaging uses electrically grounded controlled sources to produce vertical and horizontal current flow in the subsurface at the reservoir depth. The five embodiments of this technology, well known within the electromagnetic imaging community, are: (1) the LOTEM method described by K. M. Strack,
Exploration with Deep Transient Electromagnetics
, Elsevier, 1992; (2) the SIROTEM method, described by Buselli in U.S. Pat. No 4,247,821; (3) CGG's TRANSIEL® system, described in U.S. Pat. No. 4,535,5293; (4) the EMI method, described by Tasci et al. in U.S. Pat. No. 5,563,513; and (5) the WEGA-D method described by B. W. Smith and J. Dzwinel in WEGA-D SYSTEM®, WEGA-D Geophysical Research Ltd., 1984. A newer version of WEGA-D named PowerProbe® has been developed by the Canadian company Enertec, a successor to WEGA-D Geophysical Research. All five methods suffer from the vertical resolution limitation of approximately 10% of depth cited above, which makes them unsuitable for direct reservoir imaging except for unusually thick reservoirs. This resolution limitation results from one or more of the following deficiencies in each method: (1) lack of means to focus the electromagnetic input energy at the target reservoir; (2) spatial undersampling of the surface electromagnetic response fields; (3) measurement of only a few components (usually one) of the multi-component electromagnetic surface fields that comprise full tensor electromagnetic responses at each receiver (except for WEGA-D/PowerProbe); (4) data processing using 1-D, 2-D, or pattern recognition algorithms rather than full 3-D imaging methods; and (5) lack or paucity of explicit depth information and resistivity parameter values incorporated into the data processing to constrain the inversion results.
Another serious limitatio

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