The integration of different geophysical data has the potential to provide more accurate estimate of subsurface rock properties. Several methodologies and attempts have been developed over the years with the objective of reducing exploration risk. We have developed a cooperative joint-inversion approach intended to facilitate recovery of acoustic impedance (AI) using seismic and magnetotelluric (MT) data. In this approach, the MT data provided a pathway for iteratively building large-scale low-frequency information content not directly recoverable from the seismic data themselves. The MT data provided complementary information to seismic, especially in seismically complex terrains such as overthrust belts, subbasalt and subsalt, carbonate reefs or for targets below deep cover containing limestone, concretionary layers, or basalt. On the other hand, the seismic data provided structural information necessary to derive accurate resistivity models from MT inversion and small-scale features during seismic impedance inversion. The connections between resistivity and the elastic property of rocks are obtained from petrophysical relationships derived from available borehole data, or if not available, from empirical relationships. We tested our technique on synthetic and field data. The application of cooperative joint inversion to 3D seismic and MT data sets acquired in a mineral province made it possible to recover AI distribution across a wide range of geologic environments. The resulting rock property images provided a direct link to geology that is exceedingly difficult, if not impossible, to extract from the individual data sets.

Three-dimensional vertical seismic profiling data acquired from an oilfield located in Abu Dhabi, United Arab Emirates, were used to obtain a high-resolution multioffset azimuthal estimate of compressional seismic wave attenuation. On the basis of the assumption that the fracture strike corresponds to the azimuthal direction φ0 at which the attenuation is minimized, fracture orientations were obtained in three reservoir units. Two approaches were used to determine φ0: first from the variation of the absolute attenuation Q−1 with the azimuth and second from the variation of the relative attenuation ΔQ−1 with the azimuth. The rose diagrams of φ0 estimated from the Q−1 variation indicated better agreement with those showing the strikes of open and cemented fractures obtained from core interpretation than with either of those showing the two types of fractures separately. However, the rose diagrams of φ0 estimated from the variation of ΔQ−1 were more similar to those showing the strikes of open fractures obtained from core and Fullbore Formation Microimager data. This observation can be explained by the fact that in the first approach, all types of fractures contribute to the scattering and fluid-related mechanisms of Q−1. However, in the second approach, φ0 is obtained from a least-squares fitting of the variation of ΔQ−1 with the azimuth, which is based on the squirt flow mechanism that is caused by the movement of fluid between grain pores and fractures. Therefore, a comparison of the orientations obtained using these two approaches can be an efficient way to separately determine the orientations of open and cemented fractures.

Previous studies performed in Abu Dhabi oilfields, United Arab Emirates, revealed the direct link of seismic wave attenuation to petrophysical properties of rocks. However, all those studies were based on zero offset VSP data, which limits the attenuation estimation at one location only. This is due to the difficulty of estimating attenuation from 3D seismic data, especially in carbonate rocks. To overcome this difficulty, we developed a workflow based on the centroid frequency shift method and Gabor transform which is optimized by using VSP data. The workflow was applied on 3D Ocean Bottom Cable seismic data. Distinct attenuation anomalies were observed in highly heterogeneous and saturated zones, such as the reservoirs and aquifers. Scattering shows significant contribution in attenuation anomalies, which is unusual in sandstones. This is due to the complex texture and heterogeneous nature of carbonate rocks. Furthermore, attenuation mechanisms such as frictional relative movement between fluids and solid grains, are most likely other important causes of attenuation anomalies. The slight lateral variation of attenuation reflects the lateral homogeneous stratigraphy of the oilfield. The results demonstrate the potential of seismic wave attenuation for delineating heterogeneous zones with high fluid content, which can substantially help for enhancing oil recovery.

Natural source electromagnetic methods have the potential to recover rock property distributions from the surface to great depths. Unfortunately, results in complex 3D geo-electrical settings can be disappointing, especially where significant near-surface conductivity variations exist. In such settings, unconstrained inversion of magnetotelluric data is inexorably non-unique. We believe that: (1) correctly introduced information from seismic reflection can substantially improve MT inversion, (2) a cooperative inversion approach can be automated, and (3) massively parallel computing can make such a process viable. Nine inversion strategies including baseline unconstrained inversion and new automated/semiautomated cooperative inversion approaches are applied to industry-scale co-located 3D seismic and magnetotelluric data sets. These data sets were acquired in one of the Carlin gold deposit districts in north-central Nevada, USA. In our approach, seismic information feeds directly into the creation of sets of prior conductivity model and covariance coefficient distributions. We demonstrate how statistical analysis of the distribution of selected seismic attributes can be used to automatically extract subvolumes that form the framework for prior model 3D conductivity distribution. Our cooperative inversion strategies result in detailed subsurface conductivity distributions that are consistent with seismic, electrical logs and geochemical analysis of cores. Such 3D conductivity distributions would be expected to provide clues to 3D velocity structures that could feed back into full seismic inversion for an iterative practical and truly cooperative inversion process. We anticipate that, with the aid of parallel computing, cooperative inversion of seismic and magnetotelluric data can be fully automated, and we hold confidence that significant and practical advances in this direction have been accomplished.