STRUCTURE MODELLING OF SUBSURFACE BY USING KIRCHHOFF MIGRATION  METHOD AND FINITE DIFFERENCE ANISOTROPY METHOD

<p class="abstrak">The image of subsurface with a migration method keeps on developing to get an image result which the closest in real condition. The conditions in subsurface are very complex and variables it couses the process of wave propagation which can not be judged as the same in every layers. so it is needed an anisotropy pharameter analysiz (η) in seismic data migration process. The research will compare two kinds of migrations those are Kirchhoff migration and finite difference anisotropy. It is done because not all datas are processed by anisotropy, even with isotropi it will get good result. The result of kirchoff migration has not so good quality (low resolution) on the first layer reflector.but on the second and third layer reflector have good result (high resolution). I estimate that in the first layer reflector there is anistropi influence, because the ratio effect between far offset and the depth is hight. The analysis result get η ansotropi pharameter result as 0,25 and put into migration process. On the second migration process is finite difference anisotropy appears on the first layer reflector and shows high resolution and suitable with the real layer model.</p>

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Streamline-based integration of time-lapse seismic and production data into petroleum reservoir models

Geophysics ◽

10.1190/geo2011-0346.1 ◽

2012 ◽

Vol 77 (6) ◽

pp. M73-M87 ◽

Cited By ~ 10

Author(s):

Alvaro Rey ◽

Eric Bhark ◽

Kai Gao ◽

Akhil Datta-Gupta ◽

Richard Gibson

Keyword(s):

High Resolution ◽

Finite Difference ◽

Seismic Data ◽

Time Lapse ◽

Seismic Inversion ◽

Absolute Permeability ◽

Production Data ◽

Petroleum Reservoir ◽

Seismic Surveys ◽

Fluid Saturation

We have developed an efficient approach of petroleum reservoir model calibration that integrates 4D seismic surveys together with well-production data. The approach is particularly well-suited for the calibration of high-resolution reservoir properties (permeability) because the field-scale seismic data are areally dense, whereas the production data are effectively averaged over interwell spacing. The joint calibration procedure is performed using streamline-based sensitivities derived from finite-difference flow simulation. The inverted seismic data (i.e., changes in elastic impedance or fluid saturations) are distributed as a 3D high-resolution grid cell property. The sensitivities of the seismic and production surveillance data to perturbations in absolute permeability at individual grid cells are efficiently computed via semianalytical streamline techniques. We generalize previous formulations of streamline-based seismic inversion to incorporate realistic field situations such as changing boundary conditions due to infill drilling, pattern conversion, etc. A commercial finite-difference flow simulator is used for reservoir simulation and to generate the time-dependent velocity fields through which streamlines are traced and the sensitivity coefficients are computed. The commercial simulator allows us to incorporate detailed physical processes including compressibility and nonconvective forces, e.g., capillary pressure effects, while the streamline trajectories provide a rapid evaluation of the sensitivities. The efficacy of our proposed approach was tested with synthetic and field applications. The synthetic example was the Society of Petroleum Engineers benchmark Brugge field case. The field example involves waterflooding of a North Sea reservoir with multiple seismic surveys. In both cases, the advantages of incorporating the time-lapse variations were clearly demonstrated through improved estimation of the permeability heterogeneity, fluid saturation evolution, and swept and drained volumes. The value of the seismic data integration was in particular proven through the identification of the continuity in reservoir sands and barriers, and by the preservation of geologic realism in the calibrated model.

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High performance seismic data migration for high resolution interpretation

10.29118/ipa.2478.263.301 ◽

2018 ◽

Author(s):

C.N. Chernoff

Keyword(s):

High Resolution ◽

Seismic Data ◽

High Performance ◽

Data Migration

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Elastic Gaussian-beam migration for four-component ocean-bottom seismic data

Geophysics ◽

10.1190/geo2018-0716.1 ◽

2019 ◽

Vol 85 (1) ◽

pp. S11-S19

Author(s):

Xingchen Shi ◽

Weijian Mao ◽

Xulei Li

Keyword(s):

Boundary Condition ◽

Gaussian Beam ◽

Seismic Data ◽

Data Migration ◽

Ocean Bottom ◽

Elastic Wave Equation ◽

Processing Cost ◽

Migration Method ◽

Data Separation ◽

Gaussian Beam Migration

Multimode and multicomponent elastic Gaussian-beam migration is attractive for its efficiency, flexibility, and accuracy. However, when it is used for ocean-bottom seismic data, the incomplete boundary condition will yield some nonphysical artifacts in the final migrated images. To solve this problem, we extend the elastic Gaussian-beam migration method from 3C to 4C by introducing the pressure recording to represent the stress tensor on the ocean bottom. Based on the elastic wave equation and the complete boundary condition for the ocean-bottom model, we derive effective formulas of accurate multimode wave downward continuation. With our method, different wave modes are separated and the receiver ghost is removed simultaneously by applying a decomposition matrix to 4C data during the migration without prior data separation and deghosting, which eliminates the artifacts better and reduces the processing cost. Three synthetic experiments were provided to validate the method for 4C ocean-bottom data migration.

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A collocation formulation of wave equation migration

Geophysics ◽

10.1190/1.1440971 ◽

1979 ◽

Vol 44 (4) ◽

pp. 712-721 ◽

Cited By ~ 3

Author(s):

K. Pann ◽

Y. Shin ◽

E. Eisner

Keyword(s):

Wave Equation ◽

Finite Difference ◽

Collocation Method ◽

Seismic Data ◽

Space Time ◽

Basis Functions ◽

Data Migration ◽

Continuous Space ◽

Finite Difference Formulation ◽

Crank Nicolson

In solving the scalar wave equation in differential form for the purpose of seismic data migration, we apply the method of collocation to an upcoming wave equation which Claerbout introduced. In this method, a solution is written as a linear combination of a set of prescribed basis functions, and the upcoming wave equation is satisfied at a discrete set of space‐time points. We then demonstrate that, when certain multidimensional spline functions are used as the basis functions, the collocation method becomes algorithmically equivalent to a preferred Crank‐Nicolson finite‐difference formulation. Because of this equivalence, the mathematical procedures performed in the finite‐difference formulation can be reinterpreted from the point of view of the collocation method. The selection of parameters for the rational approximation of the second derivative in the preferred Crank‐Nicolson finite‐difference formulation has been based only on empirical judgment of the interpretability of the migrated seismic data, whereas in the collocation method, the selection corresponds to the choice of the simplest multidimensional splines as the basis functions. In addition, using the collocation method, the discrete finite‐difference solution can be naturally extended to the continuous space‐time domain by a method algorithmically consistent with the Crank‐Nicolson formulation.

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3-D Multi-Component Reverse Time Migration Method for Tunnel Seismic Data

Sensors ◽

10.3390/s21093244 ◽

2021 ◽

Vol 21 (9) ◽

pp. 3244

Author(s):

Peng Guan ◽

Cuifa Shao ◽

Yuyong Jiao ◽

Guohua Zhang ◽

Bin Li ◽

...

Keyword(s):

Seismic Data ◽

Cross Correlation ◽

Measured Data ◽

Ray Theory ◽

Reverse Time ◽

Reverse Time Migration ◽

Kirchhoff Migration ◽

Time Migration ◽

Migration Imaging ◽

Migration Method

Migration imaging is a key step in tunnel seismic data processing. Due to the limitation of tunnel space, tunnel seismic data are small-quantity, multi-component, and have a small offset. Kirchhoff migration based on the ray theory is limited to the migration aperture and has low migration imaging accuracy. Kirchhoff migration can no longer meet the requirements of high-precision migration imaging. The reverse time migration (RTM) method is used to realize cross-correlation imaging by reverse-time recursion principle of the wave equation. The 3-D RTM method cannot only overcome the effect of small offset, but also realize multi-component data imaging, which is the most accurate migration method for tunnel seismic data. In this paper, we will study the 3-D RTM method for multi-component tunnel seismic data. Combined with the modeled data and the measured data, the imaging accuracy of the 3-D Kirchhoff migration and 3-D RTM is analyzed in detail. By comparing single-component and multi-component Kirchhoff migration and RTM profile, the advantages of the multi-component RTM method are summarized. Compared with the Kirchhoff migration method, the 3-D RTM method has the following advantages: (1) it can overcome the effect of small offset and expand the range of migration imaging; (2) multi-component data can be realized to improve the energy of anomalous interface; (3) it can make full use of multiple waves to realize migration imaging and improve the resolution of the anomalous interface. The modeled data and the measured data prove the advantages of the 3-D multi-component RTM method.

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Streamline-Based Time-Lapse-Seismic-Data Integration Incorporating Pressure and Saturation Effects

SPE Journal ◽

10.2118/166395-pa ◽

2017 ◽

Vol 22 (04) ◽

pp. 1261-1279 ◽

Cited By ~ 10

Author(s):

Shingo Watanabe ◽

Jichao Han ◽

Gill Hetz ◽

Akhil Datta-Gupta ◽

Michael J. King ◽

...

Keyword(s):

High Resolution ◽

Finite Difference ◽

Seismic Data ◽

History Matching ◽

Flow Simulation ◽

Time Lapse ◽

Production Data ◽

Reservoir Properties ◽

Fluid Saturation ◽

Saturation Effects

Summary We present an efficient history-matching technique that simultaneously integrates 4D repeat seismic surveys with well-production data. This approach is particularly well-suited for the calibration of the reservoir properties of high-resolution geologic models because the seismic data are areally dense but sparse in time, whereas the production data are finely sampled in time but spatially averaged. The joint history matching is performed by use of streamline-based sensitivities derived from either finite-difference or streamline-based flow simulation. For the most part, earlier approaches have focused on the role of saturation changes, but the effects of pressure have largely been ignored. Here, we present a streamline-based semianalytic approach for computing model-parameter sensitivities, accounting for both pressure and saturation effects. The novelty of the method lies in the semianalytic sensitivity computations, making it computationally efficient for high-resolution geologic models. The approach is implemented by use of a finite-difference simulator incorporating the detailed physics. Its efficacy is demonstrated by use of both synthetic and field applications. For both the synthetic and the field cases, the advantages of incorporating the time-lapse variations are clear, seen through the improved estimation of the permeability distribution, the pressure profile, the evolution of the fluid saturation, and the swept volumes.

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