James J. Carazzone

Velocity inversion by differential semblance optimization

Differential semblance optimization (DSO) is an approach to inversion of reflection seismograms which avoids the severe convergence difficulties associated with nonlinear least‐squares inversion. The method exploits both moveout and amplitude characteristics of reflections. We have implemented a version appropriate to plane‐wave (p‐tau) seismograms and layered constant‐density acoustic earth models. Theoretical and numerical analyses of this version of DSO indicate that stable and reasonably accurate estimates of both velocity trend and reflectivity can be derived. To test DSO further, we applied it to a marine data set from the Gulf of Mexico, where the method produced results which compare favorably to well‐log information. The method can be extended to incorporate laterally heterogeneous velocity models.

Imaging CSEM data in the presence of electrical anisotropy

IMAGING CSEM DATA IN THE PRESENCE OF ELECTRICAL ANISOTROPY Gregory A. Newman * , Michael Commer * and James J. Carazzone + Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley California ExxonMobil Upstream Research Company, Houston Texas Email: ganewman@lbl.gov ABSTRACT Formation anisotropy should be incorporated into the analysis of controlled source electromagnetic (CSEM) data because failure to do so can produce serious artifacts in the resulting resistivity images for certain data configurations of interest. This finding is demonstrated in model and case studies. Sensitivity to horizontal resistivity will be strongest in the broadside electric field data where detectors are offset from the tow line. Sensitivity to the vertical resistivity is strongest for over flight data where the transmitting antenna passes directly over the detecting antenna. Consequently, consistent treatment of both over flight and broadside electric field measurements requires an anisotropic modeling assumption. To produce a consistent resistivity model for such data we develop and employ a 3D CSEM imaging algorithm that treats transverse anisotropy. The algorithm is based upon non-linear conjugate gradients and full wave equation modeling. It exploits parallel computing systems to effectively treat 3D imaging problems and CSEM data volumes of industrial size. Here we use it to demonstrate the anisotropic imaging process on model and field data sets from the North Sea and offshore Brazil. We also verify that isotropic imaging of over flight data alone produces an image generally consistent with the vertical resistivity. However, superior data fits are obtained when the same over flight data are analyzed assuming an anisotropic resistivity model.

Massively parallel electrical-conductivity imaging of hydrocarbons using the IBM Blue Gene/L supercomputer

Large-scale controlled source electromagnetic (CSEM) three-dimensional (3D) geophysical imaging is now receiving considerable attention for electrical conductivity mapping of potential offshore oil and gas reservoirs. To cope with the typically large computational requirements of the 3D CSEM imaging problem, our strategies exploit computational parallelism and optimized finite-difference meshing. We report on an imaging experiment, utilizing 32,768 tasks/processors on the IBM Watson Research Blue Gene/L (BG/L) supercomputer. Over a 24-hour period, we were able to image a large scale marine CSEM field data set that previously required over four months of computing time on distributed clusters utilizing 1024 tasks on an Infiniband fabric. The total initial data misfit could be decreased by 67 percent within 72 completed inversion iterations, indicating an electrically resistive region in the southern survey area below a depth of 1500 m below the seafloor. The major part of the residual misfit stems from transmitter parallel receiver components that have an offset from the transmitter sail line (broadside configuration). Modeling confirms that improved broadside data fits can be achieved by considering anisotropic electrical conductivities. While delivering a satisfactory gross scale image for the depths of interest, the experiment provides important evidence for the necessity of discriminating between horizontal and vertical conductivities for maximally consistent 3D CSEM inversions.

Inversion of P-SV seismic data

In a layered elastic material, density, shear velocity, and compressional velocity can be found at any depth from broadband surface measurements at two distinct, nonzero, precritical values of plane‐wave incidence angle. Layer‐stripping inversion uses three‐component surface velocity measurements generated by a polarized surface source to determine subsurface properties incrementally. The surface velocity measurements initialize a first‐order, nonlinear, matrix Riccati equation (derived from the elastic wave equation) which takes advantage of an attractive fixed‐point condition in the complex frequency plane to extract subsurface mechanical impedances. Subsurface density and velocities are recovered from the inverted impedances at two or more plane‐wave incidence angles. General properties of the matrix Riccati equation in the complex frequency plane aid in incorporating bandwidth constraints. Inversion of synthetic plane wave data from a piece‐wise continuous model illustrates inversion effects when only...

Inversion study of a large marine CSEM survey

The Brazil RC Marine CSEM survey was collected in April of 2004 for the ExxonMobil Remote Reservoir Resistivity Mapping (RM) Project. The portion of the survey reported here consisted of a total of 735 km of transmitter towlines arranged approximately on a 5 km x 5 km rectangular grid (see Figure 1). Vertical and horizontal electric field measurements were recovered at a total of 23 seafloor locations from a deployment of 36 seafloor instruments. Imaging of these CSEM data into full three-dimensional conductivity volumes represents a formidable challenge due to the subtle effects of reservoir targets, the volume of data and its large dynamic range. In this presentation, we report on an initial round of inversion results obtained using both isotropic and anisotropic (VTI) imaging methods. Our results support the need for an anisotropic model to accurately represent subsurface resistivity.

Elastic inversion of Gulf of Mexico data

An elastic inversion method baaed upon a wave equation for layered media haa been tested on seismic data from the Gulf of Mexico. Computed P-wave velocity and demity compare favorably with well log measurements at two locations, and show extremely small m&ties in depth. Inverted S-wave velocity was also computed, but no nearby shear velocity logs were available for comparison. traveltime for P-wave reflection at depth z starting from depth zo is

Remote Reservoir Resistivity Mapping - Breakthrough Geophysics For The Upstream

Abstract Marine controlled-source electromagnetic surveying has emerged as a new tool for remotely detecting reservoired hydrocarbons offshore. The technology was pioneered by university and government researchers over the past 25 years, and recently has benefited from development by contractors and the oil industry, including ExxonMobil. When integrated carefully with other geoscience information, primarily seismic, marine CSEM shows promise for adding considerable value in Upstream applications. Remote reservoir resistivity detection and imaging results from a recent ExxonMobil survey demonstrate this technology. Early Marine CSEM Development Offshore CSEM research began in the 1920s with studies of seafloor power cables, and saw the first commercial minerals survey offshore Cornwall, England a decade later. The research that led to todays commercial methods began in earnest much later, primarily at the British Geological Survey and UCSD Scripps Institution of Oceanography in the 1970s. Many other university and government groups started research on the technology about that time, and many continue to the present. Exxon began investigating marine CSEM in early 1981 using theory and computer modeling, and scoped the feasibility of field tests. Results looked promising for very deep water applications. However, the lack of suitable acquisition equipment, limited deep water opportunities, and the emphasis on the (then) new 3D marine seismic technology resulted in deferring further marine CSEM research.