Borrini, D. (Eni E&P Division, via Emilia 1, San Donato Milanese - Italy) | Cristini, A. (CRS4 - parco Scientifico e Tecnologico POLARIS - Pula (CA ) - Italy) | Follino, P. (Eni E&P Division, via Emilia 1, San Donato Milanese - Italy) | Marchetti, P. (Eni E&P Division, via Emilia 1, San Donato Milanese - Italy) | Zamboni, E. (Eni E&P Division, via Emilia 1, San Donato Milanese - Italy)
Summary 3D Zero-Offset Common Reflection Surface Stack (3D ZO CRS) stacking technique has demonstrated, through the last few years, to improve the imaging quality with respect to the conventional NMO/DMO processing. It is a full data driven approach, particularly efficient and robust in case of poor S/N and low coverage data and it properly handles, in amplitude preserved way, cases characterized by lateral velocity variations and structural complexity. The 3D CRS technique, now implemented at industrial level, is becoming in ENI a widely applied processing step. In this paper we show the results for two medium-low fold datasets, characterized by different S/N ratio and geological framework. The improvements of the overall structural images obtained with a Post-Stack Time Migration of the 3D CRS stack when compared to 3D NMO/DMO Post-Stack Time Migration (first case) or 3D Pre-Stack Time Migration (second case) are clearly visible in the results.
Autoregressive (AR) extrapolation is tested using a synthetic tomography example with a cross-borehole geometry. Previous work by Menke (1984) showed that cross-borehole tomography has a limited resolution in the cross hole direction. We first apply AR extrapolation to partial data and then compare tomographic inversions using the full data and the extrapolation data. Both the overall pattern of the extended data and the tomographic reconstruction with the extended data show that AR extrapolation can effectively extend the synthetic crossborehole tomographic data to a broader coverage and can improve the cross-hole resolution of the reconstruction.
SEG/Houston 2005 Annual Meeting 1246 EDITED REFERENCES Note: This reference list is a copy-edited version of the reference list submitted by the author. Reference lists for the 2005 SEG Technical Program Expanded Abstracts have been copy edited so that references provided with the online metadata for each paper will achieve a high degree of linking to cited sources that appear on the Web.
Over the past few years, multicomponent data have been used increasingly in the development of heavy oil projects, either for improved noise attenuation methods (Kendall, 2005) or for the additional information that the multicomponent seismic provides the interpreter. One of the challenges with multicomponent seismic data is understanding and managing and interpreting the large variety of attributes that can be derived from the data, especially if AVO and inversion attributes are also pursued. This paper is intended to present a workflow that was used to distill the large variety of attributes from multicomponent seismic data down to a manageable reservoir model that can be used to address a common development problem in heavy oil reservoirs. Using multiattribute analysis techniques, it is possible to identify which seismic attributes correlate to the geologic question proposed, and, using the results of the first analysis, derive an estimate of the geology present within the reservoir, in this case, shale volume (Vsh). Described below is the proposed workflow along with some of the results of this analysis.
PetroChina conducted a multichannel large-offset 2-D seismic survey in the Yumen Oil Field, Northwest China, in September, 2004. The objective is to delineate the complex, imbricate structure associated with the Yumen reservoir beneath the high-velocity Kulong Shan allocthonous rocks so as to accurately position production wells in the future. The data were acquired using a common-spread recording geometry whereby the receiver spread was fixed for all shots. A total of 1,401 receiver groups was placed along a 28,000-m line traverse in the SSW-NNE dominant structural dip direction at a 20-m interval. A total of 211 shots was fired at a 200-m interval along the line traverse, beginning at a location outside the spread and 7 km away from the first receiver group in the SSW end of the line. The distance between the first and last shot locations is 42,000 m.
We analyzed the Yumen large-offset data for earth modeling and imaging in depth. By a nonlinear first-arrival traveltime tomography, a velocity-depth model was estimated for the near-surface. Then, a subsurface velocitydepth model was estimated based on rms velocities derived from prestack time migration of shot gathers combined with half-space velocity analysis to improve the accuracy of velocity estimation below the complex overburden structure associated wth the high-velocity Kulong Shan rocks. An attempt also was made to model not just the near-surface but also the subsurface by the application of nonlinear traveltime tomography to first-arrival times picked from all offsets. Finally, prestack depth migration of shot gathers from a floating datum that is a close representation of the topography was performed to generate the subsurface image in depth.
The pressure sensitivity of rock elastic properties and seismic velocities is dependent upon pore space, grain size, grain sorting and cementation. An increasing effective pressure gradually reduces the throats between pore. It forces closure of compliant pores with low aspect ratio and reduces porosity. It also changes contact configuration that brings more cement in load bearing network. Present study models stress dependent velocity changes through this mechanical rearrangement of pore and contact system.
Although a granular rock is likely to have pore with a spectrum of aspect ratio, we put forward the concept of an ‘effective aspect ratio’ that simulates the rock elastic behavior. Such ratio can be inverted through effective medium solution. It is observed that the effective aspect ratio increases with increasing pressure due to gradual closure of compliant pores having low aspect ratio. This inturn reflects into stress sensitivity of velocities. Using dry core measurements of shear and compression velocities on variety of sandstone under multi-pressure conditions, the validity of proposal is demonstrated.
The present work also suggests a stress dependent matrix shear modulus. It accounts for the changing inter-granular frictional force and grain slippage/rotation tendencies, and varying cement contacts in matrix network. It is concluded that matrix shear modulus is significantly affected under low to moderate stress conditions, while changes are small in well cemented granular rocks. The varying aspect ratio and matrix shear modulus can be represented by uniform power laws and govern the changing velocities. It provides a rock intrinsic view to explain the stress dependent elastic behavior and is found applicable to sandstone with different cementation and porosity.
Summary Seismic modeling experiments were performed to understand the seismic responses associated with a variety of subsurface conditions. These include effect of vertical velocity gradient, horizontal velocity gradient, horizontal density gradient, variation in shot depth for reflection response, velocity model dependency on log segmentation, effect of using different wavelets for seismic response and seismic imaging of the top of a reservoir below a gas cloud using a walkaway VSP configuration. Substantial effort was devoted to the different modeling exercises to generate the synthetic data which was later processed for the given objective. Seismic modeling forms an important part of routine and special processing and in quality assurance and such exercises enhance that understanding. Introduction Seismic modeling is essentially the construction of geologic computer models and simulating their seismic wave propagation response.
Ray-Based Stochastic Inversion (RBSI) was introduced in Verdel et al. (2004) as a new seismic inversion method for reservoir parameter estimation claimed to be more accurate than conventional Stochastic Inversion (SI) in laterally heterogeneous subsurfaces. In this paper, an RBSI-variant is presented which utilises a 1D convolutional forward-modeling kernel as found in common inversion software, offering great practical benefits. Synthetic datatests demonstrate the superiority of this variant, in its proper application regime, over SI in resolving reservoir-layer- P-velocities and thicknesses in strongly dipping subsurface structures. SI, under those circumstances, is severely affected by wavelet distortion due to migration.