Pseudo-acoustic curve rebuilding and sparse pulse joint inversion method

Abstract

The invention provides a pseudo-acoustic curve rebuilding and sparse pulse joint inversion method, and belongs to the field of reservoir prediction research. The method comprises the following steps of: 1, performing cross analysis on an acoustic curve and a natural gamma-ray curve; performing statistics on a mathematical relationship of an acoustic parameter and a natural gamma-ray parameter according to the cross analysis; if the two curves have good consistency, regarding that the oil and gas reservoir prediction by the natural gamma-ray curve is effective; and entering the second step; 2, using a wavelet multi-scale transform and information fusion technology to rebuild a DT curve (acoustic-time difference curve) to obtain a pseudo-acoustic curve, wherein the curve includes both natural gamma-ray features and acoustic features; and 3, performing sparse pulse seismic inversion under the DT curve constraints to obtain a final inversion result.

Description

technical field [0001] The invention belongs to the research field of reservoir prediction, and specifically relates to a joint inversion method of pseudoacoustic curve reconstruction and sparse pulse inversion, which combines pseudoacoustic curve reconstruction and sparse pulse inversion technology to carry out reservoir prediction work, thereby improving the accuracy of reservoir prediction . Background technique [0002] The wave impedance inversion method started in the late 1970s and became popular in the 1980s. In the early days, it was mainly ordinary recursive methods (such as VELOG, SEISLOG, etc.) and sparse pulse methods (such as MED, AR, MLD, BED, etc.). The feature of this technology is to invert directly from seismic data. The logging data is mainly used for calibration. The resolution of the inversion result is directly limited by the frequency bandwidth of the seismic data. The resolution of the inversion wave impedance is relatively low, generally between 20...

AI Technical Summary

Problems solved by technology

However, with the continuous deepening of oil and gas exploration, subterranean oil and gas reservoirs, lithologic oil and gas reservoirs, and unconventional oil and gas reservoirs have become important oil and gas reservoirs of public concern, and the difficulty of exploration and prediction has also increased.

At present, using conventional model-based, iterative and other inversion methods to carry out reservoir prediction work can no longer meet the needs

In particular, the acoustic logging data is affected by the wellbore environment such as borehole collapse and mud soaking, and is also affected by the logging period, mud composition, reservoir cementation degree and porosity, and cannot accurately reflect the reservoir and surrounding rock. Differences in lithology lead to difficulties in lithology identification and reduced wave impedance resolution on the inversion profile. Even if the acoustic wave curve is corrected, in some areas, due to differential compaction and calcium content There is no significant difference in the acoustic logging curves of rocks

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