**Current Filters**

**Source**

**Conference**

**Publisher**

**Theme**

**Author**

- Al-Shuhail, Abdulatif A. (1)
- Alhukail, Ibrahim A. (1)
- Ali, Essahlaoui (1)
- Antoine, Marache (1)
- Aramco, Saudi (1)
- Calandra, Henri (1)
- Choi, Yunseok (1)
- Colette, Sirieix (1)
- Denel, Bertrand (1)
- Ferretti, A. (1)
- Gibson, Richard L. (1)
- Harris, Jerry M. (1)
- Hua, Biaolong (1)
- Jang, UGeun (1)
- Joëlle, Riss (1)
- Juan Luis, Fernandez Martinez (1)
- Leveille, Jacques (1)
- Liu, Jonathan (1)
- Min, Dong Joo (1)
- Morton, Scott (1)
- Novali, F. (1)
- Ouassima, Harmouzi (1)
- Oyler, Mike (1)
- Palacharla, Gopal (1)
- Quan, Youli (1)
- Rocca, F. (1)
- Shekhar, Ravi (1)
- Shi, Mingjuan (1)
- Shin, Changsoo (1)
- Vasco, D.W. (1)
- Yang, Dinghui (1)

to

Go **Concept Tag**

- algorithm (4)
- algorithm result (1)
- amplitude (1)
- approach (1)
- array (2)
- arrival (1)
- Artificial Intelligence (1)
- basin (1)
- beam (1)
- center (1)
- change (1)
- chemical flooding (1)
- computational (1)
- computational domain (1)
- configuration (2)
- correlation (1)
- correlation coefficient (1)
- correlation distance (1)
- covariance (1)
- data (2)
- deformation (1)
- depth (3)
- DFN (1)
- diffusion equation (1)
- dispersion (1)
**distance (9)**- distribution (1)
- electrode (1)
- element (1)
- energy (1)
- EnKF (1)
- ensemble (1)
- ensemble Kalman filter (1)
- equation (5)
- estimate (1)
- Figure (7)
- formation evaluation (2)
- fracture (1)
- fracture network (1)
- frequency band (1)
- function (3)
- geologic modeling (3)
- geometry (1)
- geophone (1)
- geophone array (1)
- geophone patch (1)
- grid point (1)
- image point (1)
- Imaging (1)
- impedance (1)
- increment (1)
- injection (1)
- inverse problem (1)
- inversion (3)
- Inversion Algorithm (1)
- inversion method (1)
- iteration (1)
- Kirchhoff beam migration (1)
- Kirchhoff Migration (1)
- Krechba field (1)
- length (1)
- location (1)
- matrix (1)
- max (1)
- method (4)
- methodology (1)
- migration (2)
- model (2)
- NAD (1)
- noise (1)
- number (2)
- optimization problem (1)
- orientation (1)
- permanent downhole sensor (1)
- permeability (1)
- Phase (1)
- plane wave (1)
- point (1)
- pressure (1)
- pressure change (1)
- production control (1)
- production monitoring (1)
- profile (1)
- ray (1)
- reference (2)
- Reinterpretation (1)
- reservoir simulation (5)
- resistivity (1)
- resistivity model (1)
- result (1)
- Saiss basin (1)
- Schlumberger (1)
- seismic modeling (3)
- source (2)
- time (2)
- traveltime (2)
- Vasco (1)
- velocity (3)
- velocity model (2)
- Waveform Inversion (1)

to

GoWe used the beam methodology to develop multi-arrival Kirchhoff beam migration. Compared to conventional single-arrival Kirchhoff migration, our method is able to handle multi-arrivals caused by model complexity. We provide a formula for optimal beam width that achieves both accuracy and efficiency. The resulting structural imaging in sub-salt areas is of better quality than that from single-arrival Kirchhoff migration.

Kirchhoff migration is an efficient and practical tool for depth imaging, but conventional implementations suffer in areas of complicated geology, since only single arrivals are used in the implementation. In conventional approaches, rays are traced from a surface point to imaging points in the subsurface. The traveltime table for imaging points is generated by ray tracing, and the input seismic trace is projected to these image points according to the calculated traveltimes. When more than one ray passes an image point, only one ray path may be chosen (either first arrival or most-energetic arrival). In this way, only one seismic arrival is associated with each image point. Therefore, some energy corresponding to other arrivals may be missing or mis-positioned during the imaging process. Multi-arrival traveltimes, from a source (or detector) to an image point, may be used to overcome the problems associated with a single-arrival traveltime (Xu et. al., 2001). However, in general, this approach has issues in a production environment since multi-valued traveltimes are difficult to store and interpolate (Gray et. al., 2002).

Beam migration has advantages in handling multi-arrival energy in imaging (Hill, 1990). Here we use the beam methodology to provide multi-arrivals in Kirchhoff migration. In our approach, the input wavefield near a surface point is decomposed into local plane waves by local slant stacking, and each plane wave contributes to one potential single-arrival in Kirchhoff migration. For each plane wave, a central ray is traced from the surface point to imaging points in the subsurface, and the traveltime in a neighborhood along the central ray is calculated. The input seismic plane wave is projected to image points according to the calculated traveltime; since each plane wave corresponds to one arrival, the imaging process uses the energy of all arrivals. In this way, a seismic trace can contribute many times to an image point through all the arrivals, with each arrival being associated with one plane wave. To maintain accuracy and efficiency, each plane wave propagates only within a beam, which is defined by a neighborhood along the central ray. The choice of the width of the beam is critical to the implementation of Kirchhoff beam migration. We choose an optimal beam width using the criterion that the summation of all beams is sufficient to provide minimum coverage of the imaging area. Here, we derived a formula that computes the optimal beam width from ray tracing.

The input seismic data can be decomposed into local plane waves at beam centers by using local slant stacking. Data regularization is necessary for such processing. The input data are sorted into common-offset panels, with one trace per bin center in each panel.

arrival, beam, distance, equation, image point, Imaging, Kirchhoff beam migration, Kirchhoff Migration, migration, plane wave, point, ray, source, traveltime, velocity

SPE Disciplines: Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)

In order to describe the irregular topography that is commonly encountered in land-based seismic exploration, we present a frequency-domain elastic wave modeling algorithm for this phenomenon, incorporated into an elastic waveform inversion algorithm. We use a finite-element method, both for the modeling and for the inversion algorithms, in which the main body is approximated by rectangular elements and irregular topography is described by triangular elements. In common with conventional finite-element modeling algorithms, our finiteelement irregular topography modeling algorithm also naturally satisfies the free-surface boundary condition due to the Neumann boundary condition, which is incorporated when we construct the finite-element formulae. For the inversion algorithm, we use the steepest-descent method, and scale the gradient direction using the diagonal of the pseudo-Hessian matrix rather than the approximate or full Hessian matrix. We apply the inversion technique to the AA-line of the SEG/EAGE salt dome model, modified to account for irregular surface topography. Through numerical examples, we demonstrate that our elastic waveform inversion can reproduce subsurface structures and elastic parameters fairly well, even for a model with irregular topography.

Seismic waveform inversion is an iterative procedure that is used to obtain the physical properties of a subsurface medium by fitting observed data to modeled data. This procedure requires a reliable seismic modelling algorithm for its effective use. Irregular topography is commonly observed in land-based seismic exploration, and this affects the seismic modelling and inversion results. If surface topography data exist for an area of interest, this needs to be described properly in the seismic modelling and inversion algorithms. For irregular topography modelling algorithms, finite-difference elastic modelling methods have been developed by Hestholm and Ruud (1994), Ruud and Hestholm (2001), Oprsal and Zahradník (1999) and Pérez-Ruiz et al. (2005) while Ichimura et al. (2007) proposed a finite-element method. All of these are time-domain methods.

Recently, however, several frequency-domain waveform inversion algorithms have been developed. These require a frequencydomain modelling algorithm. Frequency-domain algorithms may have the advantage of being effective for describing a model with multiple sources. Parallel processing can also be performed relatively easily by distributing the processors over the different frequencies. Moreover, in frequency-domain waveform inversion, the source wavelet and model parameters can easily be estimated, which helps us to achieve better convergence in our models. For these reasons, we developed a frequencydomain elastic wave modelling algorithm for an irregular topography, and incorporated it into an elastic inversion algorithm. For the modelling and inversion algorithms, we used a finite-element method. Such methods have been shown to deal correctly with free-surface boundary conditions, without any additional stress-free boundary conditions. For conventional finite-element elastic wave modelling algorithms describing a flat free surface, we usually use a rectangular element set. However, for irregular topography, rectangular element sets can be problematic because slopes are then described by stair shapes that may cause artificial reflections. To overcome this, we use triangular elements for irregular topography and rectangular bilinear elements for subsurface structures.

SPE Disciplines: Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)

A stochastic approach to seismic inversion using the ensemble Kalman filter (EnKF) is proposed. Seismic depth and time image data are used as the input for EnKF stochastic seismic inversion. The sonic log is used to estimate source wavelet and create initial models for the inversion, which provides an efficient integration of sonic log data and seismic data. We use both travel time and waveform data for the inversion and obtain the absolute seismic velocity instead of the relative impedance. EnKF can continuously update the model using time-lapse data. A synthetic example is used to demonstrate the possible application to seismic monitoring.

covariance, data, depth, distance, EnKF, ensemble, ensemble Kalman filter, equation, Figure, formation evaluation, impedance, inversion, model, permanent downhole sensor, production control, production monitoring, reservoir simulation, seismic modeling, traveltime, traveltime data, velocity, velocity model, waveform, well logging

Oilfield Places:

- South America > Brazil > Brazil Offshore > Campos Basin (0.99)
- North America > United States > Wyoming > Powder River Basin (0.99)
- North America > United States > Montana > Powder River Basin (0.99)

SPE Disciplines: Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)

Knowledge of the orientation and spatial distribution of fractures in rocks is important for predicting the flow of fluids. Masihi et al. (2007) developed a new method of modeling these distributions beginning with theoretical results from the physics of fracturing. We implemented and extended this modeling technique to generate models that better incorporate field observations. The method starts with an energy function based on the pair-wise spatial correlation of fractures that also serves as an objective function for a simulated annealing algorithm (SA) that generates realizations of correlated fracture networks. We improved this technique by incorporating periodic boundary conditions, including criteria to limit maximum range of the pair-wise calculations, and by suggesting methods to constrain models to match field data. For most subsurface rocks (with Poisson ratio ? = 0.25), this method generates orthogonal sets of fractures, a pattern that is commonly observed during basin formation or subsidence. This new method is compared with conventional discrete fracture network (DFN) modeling by computing the fractal dimension of the networks. We also examine the implications for seismic reservoir characterization by computing effective seismic velocities and the resulting synthetic seismograms. The new approach can be considered better than DFN as DFN generates realizations based on only statistical distributions, without any knowledge of physics of fracturing.

The quantification of the spatial concentrations and orientations of fractures in low permeability rocks is essential since they control the nature of fluid flow in those rocks. Generally, these spatially distributed fractures form complex networks that can either act as fluid carriers or barriers depending upon fracture connectivity. Therefore, understanding the connectivity pattern, and areas of high and low fracture density zones, is essential to characterize flow inside the earth. To date much research has considered the effect of geometrical properties of fractures such as length (Berkowitz, 1995; Bour and Davy, 1997) and orientation (Balberg et al., 1984; Masihi et al., 2005) on the scaling laws of the connectivity of fractures. However, fewer studies have examined the spatial correlation of quantities such as length, orientation and position of fractures, though some of the studies examined the long-range density correlations using fractal geometry (Berkowitz et al., 2000; Darcel et al., 2003). These spatial correlation parameters are important as they affect the connectivity of fractures.

A common approach used to model fractures is the discrete fracture network (DFN) method. Generally DFN modeling specifies the statistical distributions of several parameters such as fracture density, orientation, location, size, etc. to generate several realizations for production estimation and reservoir planning (Al-Harbi et al., 2004). Here, we implement and extend a new model of the spatial distribution of fractures based on the physics of the fracturing process (Masihi et al., 2007; see also Shekhar, 2008) which is not explicitly considered in DFN modeling. The idea for modeling is based on the assumption that the elastic free energy associated with the fracture density follows the Boltzmann distribution.

SPE Disciplines:

Geophone arrays with various geophone spacings were subsequently formed from the original geophone patch. The incoherent noise was evaluated by comparing the RMS signal amplitude of the simulated geophone arrays to the RMS amplitude predicted by the square-root law. The square-root law states that summing N traces enhances the signal-to-noise (S/N) ratio by the

Results confirmed the existence of seismic-noisecorrelation- distances below which the simulated-geophonearray- trace curve raises 3 db above the square-root-law value. The seismic-noise-correlation distance is frequency dependent, increasing with decreasing frequency of the incoherent noise. Therefore, larger geophone spacing is required to attenuate low-frequency incoherent noise. The results of this study can be used to determine the optimum geophone spacing required for enhancing the S/N ratio in a specific frequency band

Deformation in the material overlying an active reservoir is used to monitor pressure change at depth. A sequence of pressure field estimates, eleven in all, allow us to construct a measure of diffusive travel time. The distribution of travel time values forms the basis for a linear inverse problem for reservoir flow properties. Application to mterferometric Synthetic Aperture Radar (InSAR) data gathered over a

Joëlle, Riss (Bordeaux Univeristé) | Juan Luis, Fernandez Martinez (Visiting professor at UC-Berkeley) | Colette, Sirieix (Bordeaux Univeristé) | Ouassima, Harmouzi (Bordeaux Univeristé) | Antoine, Marache (Bordeaux Univeristé) | Ali, Essahlaoui (Meknes University)

A series of vertical electrical soundings (VES) carried out in Schlumberger array is revisited to produce 2D resistivity model for the north central part of the Saiss Basin (Morocco). This paper is an attempt to show how data from traditional single soundings in Schlumberger configuration can be rearranged using geostatistical tools to estimate apparent resistivity values with a format compatible with a Wenner-Schlumberger array. The result is a series of estimated pseudo-sections that respect the spatial structure (covariance model) inherent in the original data set (VES), which finally are inverted to produce a 2D resistivity model of the basin along geophysical profiles. The estimated apparent resistivity field gives also valid hints about the 2D geo-electrical structure of the basin. Applying this methodology to different parallel VES profiles along the basin a 3D resistivity model can be generated.

SPE Disciplines: Reservoir Description and Dynamics > Reservoir Characterization > Geologic modeling (1.00)

In this article, we present some wave-field snapshots and synthetic seismograms by using a refined algorithm of the nearly analytic discrete (NAD) method that was proposed recently in BSSA, investigate the numerical dispersion of the refined algorithm through numerical simulations, and compare the wave-field results computed by the refined algorithm against those of the 8th-order finite-difference (FD) method. Numerical results show that the refined algorithm has no visible numerical dispersion for any space grid increments and can automatically suppress the numerical dispersion caused by discretizing the wave equation when too few samples per wavelength are used or when models have large velocity contrast.

Conventional explicit finite-difference and finite element methods for solving the acoustic- and elastic- wave equation suffer from numerical dispersion. The numerical dispersion can lower the resolution of synthetic seismograms. In order to eliminate the numerical dispersion, one way is to use sufficient grid points per upper half-power wavelength. For example, ten or more grid points per wavelength at the frequency of the upper half-power point should be adequate when the usual 2nd-order accuracy FD scheme is employed, while the 4th-order scheme seems to produce accurate results at five or six grid points per wavelength at the frequency of the upper half-power point (Alford et al., 1974). However, this way using more grid points per wavelength results in needing more computational costs and storages for computer code. Another way of attacking the numerical dispersion is to use high-order FD schemes (e.g., 8th-order FD method, Dablain, 1986) or staggered-grid FD methods (Virieux, 1986; Igel et al., 1995) or the pseudo-spectral method (PSM) (Kosloff and Baysal, 1982) to reduce the numerical dispersion. The higher-order FD or staggered-grid FD methods can further reduce the numerical dispersion, but they still suffer from the numerical dispersion when too few samples per wavelength are used (Sei and Symes, 1994). The PSM is attractive as the space operators are exact up to the Nyquist frequency. In other words, the PSM only requires 2 grid points per wavelength for eliminating the spatial numerical dispersion (Dablain, 1986). However, it also suffers from numerical dispersion in the time, and its numerical dispersion increases with increasing the time increment (Yang et al., 2006).

The so-called "nearly analytic discrete method (NADM)" (Yang et al., 2003a) and it''s improved algorithm (Yang et al., 2007) for solving the acoustic and elastic equations is another kinds of effective methods for decreasing the numerical dispersion. These methods, based on the truncated Taylor expansion and the local interpolation compensation for the truncated Taylor series, use the wave displacement-, the velocity- and their gradient-fields to restructure the wave displacement fields. Hence it enables effectively to suppress the numerical dispersion.

This paper is to present a refined algorithm of the NADM and investigate the efficient implementation of the refined NAD for these cases of heterogeneous media and very coarse space steps.

We first review and summarize the key ideas in it. The same notations as that in the original NADM (Yang et al., 2003a) in our present study,.

algorithm, computational, computational domain, dispersion, distance, equation, Figure, grid point, increment, method, model, NAD, reservoir simulation, snapshot, space, spatial, time, wavelength

Shot-record pre-stack depth migration is a standard component of our seismic imaging toolbox and has a cost proportional to the number of shots migrated. A decade ago we migrated using one-way approximations to wave propagation, commonly called "wave-equation migration", and frequently only used a fraction of the shots to control the computational cost. Today, we routinely run multiple iterations of wave-equation migration using all the shots. However, reverse-time migration, using the more accurate two-way propagation approximation, is very expensive with today''s computers when all the shots are used. Rather than migrating a subset of the shots, it is common today to combine nearby shots into a "super-shot" which can be migrated at the cost of a single shot. One simple method for creating a super-shot is to bin the shot locations. In this paper, we present an algorithm for optimizing the grouping of shots, generally resulting in fewer super-shots and/or less shot movement when compared with shot binning.

Thank you!