This paper develops a method of joint inversion of airborne gravity gradiometry and magnetic data using Gramian constraints. The joint inversion technique reduces the non-uniqueness in the potential field inversion. The Gramian constraints make it possible to consider different correlations between multimodal geophysical parameters. The model study demonstrates that the joint inversion produces better results if one uses a logarithmic relationship between the density and magnetic susceptibility instead of a linear one. In the case of a body with strong remnant magnetization, one should consider inverting for the magnetization vector instead of a simple susceptibility inversion. This situation has been analyzed with both model and case studies. The case study includes joint inversion of airborne gravity gradiometry and magnetic data from the Lac de Gras region of the Northwest Territories of Canada, where the target kimberlites are characterized by strong remnant magnetization.
Seismic data acquisition and processing must be tuned for the target interval and under certain conditions that interval can be extended, but processing approaches employed must be compatible with the limits of the data and acquisition equipment. With a virtually unlimited number of recording channels currently available and the power of processing approaches commonly used for noise suppression and signal enhancement, the temptation to consider seismic reflection data acquired with close-spaced sensors and broadband, energetic sources useful for all depth ranges (near surface to exploration depths) is flawed. Zero- or near-zero offset traces are rarely populated with reflection signal that can be extracted from source noise or, worse yet, the most significant bits are truncated via clipping. Even with the most modern seismographs, near-offset traces are routinely clipped due to source energy levels. A common practice of only recording (or at least only using) field-correlated vibroseis data disguises dramatic and damaging pitfalls when near-offset signal is critical to imaging intervals and used without regard to the fitness of all the raw data traces. Near-surface seismic reflection imaging can only be accomplished using data specifically or at a minimum secondarily tuned to the recording system, sensors, source, spacing, and optimum offset range for the target reflection time and offset interval.
In the past, the anisotropy community has asserted that we are unable to distinguish between the effects of stress-aligned vertical micro-cracks (arising from unequal horizontal stresses), and vertical aligned macro-fractures that flow fluids. This assertion is one manner of phrasing the hypothesis that we are unable to determine the scale (size) of the fracture causing the azimuthal anisotropy. This paper asserts: 1) that the result of unequal horizontal stress is azimuthal traveltimes, best quantified as P-P azimuthal interval velocities following azimuthal prestack depth migration, and 2) that the information concerning vertical aligned macro-fractures that flow fluids is best evident in azimuthal amplitudes (P-P, etc.) of said processed data, with the caveat that all the standard issues of bed thickness, removal of noise, preservation of signal, temporal resolution, and spatial resolution constrained by the proper bin size, given a geologic dip on the beds, a fold, and offsets equal to target depths, are present and operative. Having looked at azimuthal reflection seismic data for more than thirty years, and having seen a consistent pattern in field data, I offer the above two assertions as hypotheses to be tested against current and future datasets, both field data and model data, provided that these model data come from algorithms using orthorhombic, monoclinic and/or triclinic symmetries.
Tiwari, Arjun (Cairn India Limited) | Harshvardhan, _ (Cairn India Limited) | Mukherjee, Supriya (Cairn India Limited) | Keidel, Steve (Cairn India Limited) | Goodlad, Stephen (Cairn India Limited) | Kumar, Sanjay (Cairn India Limited) | Ghosh, Arnab (Cairn India Limited)
Integration of all subsurface datasets is paramount for building robust reservoir models. These datasets include well, 3D seismic and dynamic data, which taken together form the basis of an integrated reservoir model. Of critical importance in the construction of a reservoir static model is getting the structure right. Towards that goal, we present an example of the Bhagyam field in Rajasthan, India, where horizon based illumination maps have provided both structural and stratigraphic insight where other more conventional attributes, such as time slices or dip /azimuth maps, have fallen short.
The advanced workflows undertaken aided in identifying structural complexity that was not previously captured in early Bhagyam reservoir models. Part of the problem with the early reservoir models was that most of the well data used to build them were drilled above the OWC, owing to the use of screen completions. This resulted in partial penetration of the reservoir. Later, as the completion strategy changed to cased and perforated, wells with full penetration of the reservoir were drilled. These deeper wells provided insight on fault cut outs which was not previously possible. The orientation of faults were interpreted on seismic with the aid of horizon based dip illumination maps, constructed from the seismically most well defined and therefore most confidently interpreted and auto tracked seismic reflections, at or near the reservoir interval. A determination was then made as to whether key faults in the field, with the aid of time varying depletion and water cut data, acted as a conduit or a barrier to fluid flow. The final framework model incorporated all the above datasets in helping to build a robust static as well as simulation model.
In the presence of a highly-scattering near surface, standard imaging techniques often do not succeed in producing accurate images of deeper targets. Improved images could be obtained removing the effect of the complex overburden from the data, but this requires a detailed velocity model for such a portion of the subsurface. Recently, a novel approach for retrieving the Green’s function in an unknown medium from the reflection response measured at the acquisition surface and an estimate of the propagation velocity. These redatumed wavefields are redatumed below the complex near surface and then used as input for a finite-difference (FD) injection technique. This injection process will allow imaging techniques based on forward- and back-propagation, such as reverse-time migration (RTM), to produce a more accurate image of deeper targets. We introduce a workflow for the proposed method and illustrate its application with a numerical example based on a simple layered model.
We show that ambient seismic noise can be used to detect long-term velocity changes in Scholte-wave velocities at microseism frequencies. Two approaches to detect a time-lapse change in Scholte-wave velocities are tested: a data-domain and an image-domain approach. We rely on straight-ray tomography of perturbed traveltimes for imaging. The first approach is based on differentiating phase traveltime changes in the data domain. The second approach is based on differentiating group velocities in the image domain. Both methods work very well and compare well to a time-lapse image computed from controlled-source data. The time-lapse response is dominated by near-surface geomechanical effects of production-induced reservoir compaction.
Wave equation migration can usually produce high-quality images below complex overburden given sufficient data and an accurate velocity model. However, inaccurately estimated high-contrast, short-wavelength, buried velocity anomalies disrupt the images of seismic reflections from deeper layers. Currently we solve this problem by building velocity models either with tomographic techniques or interpretation-based techniques. Existing velocity model construction methods based on interpretation and insertion of complex model boundaries are time consuming, tedious to implement, and error-prone. More-automated velocity model construction methods such as tomography (Stork, 1992), wave equation migration velocity analysis (Biondi and Sava, 1999) and FWI (Sirgue and Pratt, 2003) tend not to have enough resolution to define boundaries with sufficient sharpness, or may not have sufficient depth of investigation to handle very complex velocity boundaries at arbitrary locations in the model.
In the exploration and development of oil and gas fields, the nature of the local micro tectonics is one of the key factors that determines the distribution of remaining oil. In general, micro tectonics can be divided into positive microscopic structural and negative microscopic categories. The former is considered to be an area with abundant remaining oil and the second category is an area that is poor in oil and gas reserves or is easily flooded by water. In this paper, we propose an automatic method to identify positive micro structural regimes, and calculate related parameters. The proposed method generalizes a watershed transformation - an image segmentation technique based on the simulation of flooding of a landscape - into the field of seismic exploration. The method not only improves the recognition accuracy of positive micro tectonics, but greatly reduces the manual participation, which, in turn, provides reliable data for injection-production schemes and calculation of remaining reserves. Finally, we illustrate the proposed method using one real 3-D seismic data set. The results show that improved models based on the watershed theory can identify positive micro tectonics with high accuracy.
Conventional high-order discontinuous Galerkin schemes suffer from interface errors caused by the misalignment between straight-sided elements and curved material interfaces. We develop a novel discontinuous Galerkin scheme to reduce the errors. Our new scheme use the correct normal vectors to the curved interfaces, while the conventional scheme uses the normal vectors to the element edge. We modify the numerical fluxes to account for the curved interface. Our numerical modeling example demonstrate that our new discontinuous Galerkin scheme significantly suppresses the spurious diffractions seen in the results obtained using the conventional scheme. The computational cost of our scheme is similar to that of the conventional scheme. Our new discontinuous Galerkin scheme is thus particularly useful for large-scale scalar-wave modeling involving complex subsurface structures.
Multi-wave seismic exploration is an integrated method that uses P-waves, S-waves, and converted waves to accomplish precise exploration of petroliferous basins and directly predict the location of hydrocarbons. This paper presents a successful example of three-component three-dimensional (3C3D) seismic exploration of a fractured-cavity carbonate reservoir in the northern part of the Tarim Basin in China. We use the different characteristic responses between P-waves and converted waves in fractured-cavity carbonate reservoirs and the converted-wave seismic imaging technique to achieve better imaging in fractured-cavity carbonate formations. The techniques of converted-wave seismic imaging applied in this work include converted-wave static correction, multi-parameter velocity analysis of converted waves, and anisotropic pre-stack time migration (PSTM).