1887

Abstract

Summary

The algae beach dolomite reservoir, with great exploration potential, is widespread developed in the study area, which is located in the northwest of Sichuan Basin. The reservoir of Triassic Leikoupo formation is strong heterogeneity, and the lateral distribution is discontinuous. Meanwhile, the seismic response characteristics are not absolutely clear, sonic logging shows no obvious difference between reservoir and non-reservoir, which is increase the prediction difficulty. Therefore, we utilize a series of methods, such as seismic modeling, high resolution waveform indication inversion and spectral decomposition hydrocarbon detection methods, to predict the reservoir. Firstly we establish multi-wells model to obtain the seismic response features of algae beach reservoir that is weak peak amplitude reflection. Then we operate high resolution waveform indication inversion, investigates unique features from both seismic waveforms and logs unlike geostatistics based on variogram, to predict the range of reservoir. At the same time, we use spectral decomposition methods to detect gas-bearing reservoir. Finally, we integrate the prediction results to comprehensively evaluate the favorable zone of the Leikoupo formation algae beach reservoir and conduct 3 design wells. In this way, we have a basic understanding of the development of algae beach dolomite reservoir in this region.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201901636
2019-06-03
2019-12-06
Loading full text...

Full text loading...

References

  1. Bi, J.J., Yang, H. and Huang, J.B.
    [2018] SMI-a high-resolution seismic inversion based on waveform indicated of reservoir geophysics. 2018 Society of Exploration Geophysicists and the Chinese Geophysical Society, 13–16.
  2. Bortoli, L.J., Alabert, F., Haas, A. and Journel, A
    . [1993] Contstraining stochastic images to seismic data. Geostatistics Tróia, 92, 325–337.
    [Google Scholar]
  3. Castagna, J.P., Sun, S. and Siegfried, R.W.
    [2003] Instantaneous spectral analysis: Detection of low-frequency shadows associated with hydrocarbon. The Leading Edge, 22, 120–127.
    [Google Scholar]
  4. Mosegaard, K. and TarantolaA
    . [1995] Monte Carlo sampling of solutions to inverse problems. Journal of Geophysical Research, 100, 12431–12447.
    [Google Scholar]
  5. Tarantola, A
    . [2005] Inverse problem theory. SIAM.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201901636
Loading
/content/papers/10.3997/2214-4609.201901636
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error