Abstract

A successful calibration process for reservoir quantification in the deep-water Gulf of Mexico has been developed with quality-control processes that validate the seismic amplitude with respect to the well-log data. These processes also provide "quick-look" answers to questions such as "Is it a salt or gas reflection?" by correlating regional petrophysical trends to various AVO attributes. The robustness of the AVO attribute or amplitude measurement can be directly related to the local petrophysical properties for providing a risk assessment.

In the deepwater GOM, this methodology can be used to calibrate the seismic response of different pore fluids. In particular it points out the sensitivity of the seismic amplitude response to not only to the presence of hydrocarbons but also the potential economic quality of the hydrocarbons.

Pore fluids produce a variety of different responses in the deepwater Gulf of Mexico and it is naive to expect hydrocarbons to have a consistent seismic amplitude signature. However by studying the geological environment and utilizing regional information carefully one can accurately predict the response for a given area.

Introduction

A purpose of a methodology is to provide a consistent set of rules to evaluate a large set of data. This is the case with our project which covers the expanse of what is commonly referred to as "the deepwater frontier of the Gulf of Mexico". Because this area encompasses a large basin, calibrating the seismic response to lithology opens a wide area to exploration.

The methodology can be broken into three parts:

  • Seismic processing with amplitude preservation of the maximum offset possible.

  • Well log curves interpretation and forward AVO modeling.

  • Calibration of processed data with model results with color map for lithology.

Seismic Data Processing

Key requirements of the processing sequence are preservation of pre-stack amplitude, elimination of coherent noise (primarily water bottom and interbed multiples), performance of sufficient velocity analysis for proper normal-moveout correction, and application of anisotropy correction for optimal alignment of ultra-far offsets (since most of the study area exhibits vertical transverse isotropy (VTI)). When possible, the processing parameters associated with each process are kept consistent. However, subtle parameter adjustments on a line-by-line basis are made, when necessary, to improve signal quality (e.g. decon window application, radon de-multiple rejection parameters). The general processing flow is listed below. Key steps are detailed in the next section.

  1. Reformat from Seg-Y DLT Tapes

  2. Geometry Application

  3. Spherical Divergence (V**2*T)

  4. Low-cut Filter (4/8 Hz)

  5. De-Spike Application

  6. FK Filter

  7. Source Signature Deconvolution

  8. Spiking Deconvolution (240 ms operator)

  9. CDP Sort

  10. Velocity Analysis (every 1000 m)

  11. RADON Demultiple

  12. Uniform Offset Stacks (every 100 m)

  13. Kirchhoff DMO

  14. FX Deconvolution

  15. Stolt FK Migration (one function)M

  16. Velocity Analysis (every 500 m)

  17. Anisotropic Long Offset NMO

  18. Mute

  19. Relative Amplitude Correction

  20. Phase Rotation (270 degrees)

  21. Final PSTM Stack (0-30 degrees)

  22. AVO products generated:

Noise Rejection

An f-k filter was applied to eliminate water bottom refractions.

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