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Reservoir Technology

RESERVOIR HIGHLIGHTS

  • Reservoir Geophysics Services were initiated at Sensor Geophysical in the fall of 2003.

  • Sensors’ Reservoir Geophysics Services for complex reservoir characterization projects are based onfull integration of seismic data with petrophysical and geological data.

  • Petrophysical well analysis has been completed for hundreds of wells.

  • Reservoir attribute analysis work has been successfully completed on 100 projects consisting of 2D lines and 3D volumes.

  • Data volumes for 3D projects have ranged from several hundred shot records to 55,000 shot records.

  • Projects reflect extensive domestic and international experience in all types of reservoirs (clastic and carbonate prospects as well as heavy oil).

RESERVOIR TECHNOLOGY

  • AVO: AVO modeling, fluid replacement modeling and attribute analysis of the pre-stack seismic response designed to estimate lithology and fluid changes on reservoir rocks.

  • Inversion: Several seismic inversion techniques including model based, sparse spike and neural network are available to produce impedance volumes that can be used to calculate Lambda-Rho (Incompressibility) and Mu-Rho (Rigidity) volumes.

  • Neural Network Analysis: Reservoir properties may be estimated with this tool using a combination of well logs and seismic attributes.

  • Registration of the PP and PS events

  • Simultaneous PP and PS Inversion

  • Multi-volume Visualization

  • Spectral Decomposition (DFT, CWT, S transform)

  • Seismic Facies Classification

  • FDA (Fracture Detection Analysis) using 3D azimuthal AVO technique (AVAZ)

RESERVOIR GEOPHYSICS WORKFLOW

AVO MODELING & FLUID REPLACEMENT MODELING

  • Comprehensive log editing and Petrophysical log transforms
  • Graphical log/seismic correlation
  • Log crossplotting for petrophysical parameter determination
  • Ray trace and full elastic wave methodologies to create full AVO offset synthetic gathers
  • Isotropic and anisotropic modeling
  • Fluid replacement modeling
  • Event picking on models for graphical comparison to seismic events
  • AVO attributes analysis of models

AVO ANALYSIS

  • Precondition the pre-stack seismic data with “AVO friendly” procedures
  • Arbitrary line viewing of gathers and partial stacks
  • Amplitude vs. offset graphs for picked events
  • Transformation between offset and angle domain
  • Range limited stacks
  • Super gather generation
  • Select the optimum AVO attributes (intercept, gradient, curvature, P-wave and S-wave Impedance Reflectivity, Fluid Factor) based on feasibility studies
  • Volume or map-based attribute analysis
  • 3D visualization of AVO attributes for quality control and interpretation
  • AVO attribute cross-plotting including mapping back to seismic of the cross-plot zones

RESERVOIR PROPERTIES - LMR

  • P-impedance, S-impedance and Elastic impedance Model design in time or depth domain based on vertical and/or deviated wells
  • Wavelet extraction and well correlation
  • Seismic inversion studies using several inversion techniques: model based, band limited, sparse spike, neural network, Lambda-Mu-Rho.
  • Computation and interpretation of a*• Results calibration to rock properties
  • Volume or map-based interpretation
  • 3D visualization of the reservoir properties volumes for quality control and interpretation
  • Volume co-rendering and cross-plotting (including mapping back to seismic of the cross-plot zone)

AZIMUTHAL AVO FOR FRACTURE DETECTION (AVAZ)

Vertically aligned fractures in the earth generate a variation in the magnitude of reflection coefficients with azimuth which is detectable on seismic data. AVAz analysis starts with 3D prestack NMO corrected or prestack time migrated CDP gathers. These gathers have to be processed using amplitude friendly flows with seismic source to receiver azimuth information preserved. The gathers used for conventional AVO analysis can be used for further azimuthal AVO analysis.

The basic mathematical model for the seismic reflection and transmission amplitude behavior is based on Ruger’s Equation (1996). This equation starts from the conventional intercept-gradient two-term AVO equation and generalizes the gradient coefficient into a function of azimuth angles. This gradient function is elliptical and the primary and secondary axes of the gradient ellipse indicate the existence, direction and strength of azimuthal anisotropy. The difference between the maximum gradient and the minimum gradient within the full azimuth range is related to the shear-wave splitting parameter, which is directly related to the crack density. When the ellipse becomes a circle, the azimuthal change of the gradient disappears and Ruger’s equation reduces to the intercept-gradient two-term equation; and this means no azimuthal anisotropy is detected.

When using AVAz analysis for fracture detection it is essential not only to know the orientation and strength of the azimuthal anisotropy; we also have to understand the lithology in order to determine the likely direction of the fractures. This is because two different perpendicular directions of fractures can generate the same AVAz response.

References:

Ruger, Reflection coefficients and AVO analysis in anisotropic media, PhD dissertation, Colorado School of Mines, 1996

Jenner E., Azimuthal AVO: Methodology and data examples, The Leading Edge, August 2002.

SOFTWARE

PROPRIETARY SENSOR GEOPHYSICAL SOFTWARE

  • FDA (Fracture Detection Analysis) using 3D azimuthal AVO technique (AVAZ).

  • TFAN (Time-Frequency Adaptive Noise Suppression) Noise attenuation module designed specifically for AVO compliant preconditioning of the pre-stack data prior to attribute analysis.

  • OCGC (Offset Consistent Gain Control) Scaling module designed for AVO compliant preconditioning.

HAMPSON-RUSSELL SOFTWARE

  • AVO

  • STRATA

  • EMERGE

  • ProMC

GEOMODELING CORPORATION SOFTWARE

  • VisualVoxAt

PUBLICATIONS

  • Dumitrescu, C.C., and Mayer, F., 2006, Case study of a Cadomin gas reservoir in the Alberta Deep Basin: Technical Abstracts of the SEG Annual Meeting 2006.

  • Dumitrescu, C.C., and Lines, L., 2006 Heavy Oil Reservoir Characterization using VpVs Ratio and Spectral Decomposition: Technical Abstracts of the SEG Annual Meeting 2006.

  • Dumitrescu, C. C., Lines, L., 2006; Vp/Vs Ratio of a Heavy Oil Reservoir from Canada; CSEG Convention 2006

  • Dumitrescu, C. C., Mayer, F., 2006; Case Study of a Cadomin Gas Reservoir (Leland) in the Deep Basin: From Deterministic Inversion to Neural Network Analysis;
    CSEG Convention 2006

  • Dumitrescu, C. C., Mayer, F., 2006; The Evolution of AVO use for Cadomin Exploration in Leland Area of Alberta;
    CSEG Convention 2006

  • Dumitrescu, C. C., Bellman, L., Williams, A., 2005; Delineating productive reservoir in the Canadian Oil Sands using neural networks approach; CSEG Convention 2005

  • Dumitrescu, C. C., Grey, D., Bellman, L., Williams, A., 2003; PS and PP AVO Analysis; A Multi-component Seismic Case Study for the Long Lake Oil Sands Project; CSEG Convention 2003