OBS-based method for long-offset distance construction of shallow water area speed model

Abstract

The invention discloses an OBS-based method for long-offset distance construction of a shallow water area speed model, and is mainly applied to a sea area with a relatively flat seabed and relativelyshallow water, OBS data collected in such a sea area are often low in signal-to-noise ratio and serious in space alias, combined with the advantages of survey line symmetry observation system design,the method (1) eliminates main clock drift distance through direct wave correction, (2) makes up for the problem that actually collected OBS gather shallow layer is serious in space alias, eliminatesresidual clock drift distance, and also solves the problem of near-offset distance first arrival pickup through forward modeling correction, and (3) solves the problem of comparison verification of medium- and far-offset distance first arrival pick through groups of different offset distances of combinations of different OBS gather through ray reciprocal comparison tracking; accurate pickup of OBS gather first arrival is fully realized; and after first arrival is picked up, a speed model is obtained through inversion during travel. The modeling method provided by the invention can obtain an accurate middle and deep part speed model, the obtained speed model is superior to a speed model obtained through speed spectrum pickup through traditional multichannel earthquake, and thus the methodis of great significance to research of complex structure imaging in oil gas exploration.

Description

technical field [0001] The invention relates to the technical field of oil and gas exploration and development, in particular to a method for constructing a shallow water area velocity model based on the long offset of OBS. Background technique [0002] In oil and gas exploration, the migration imaging of underground structures and the prediction of oil and gas reservoir parameters all rely on an accurate velocity model. However, due to: 1) the basement is deep, the effective wave energy is very weak, and the signal-to-noise ratio is low; 2) the tectonic movement near the basement is severe, and the imaging effect of the fracture zone is poor; 3) the velocity at the basement changes rapidly, picking up Inaccurate velocities lead to poor imaging effects and other reasons, resulting in deep imaging especially basement has always been a difficult point in seismic data processing. What can be done in data processing is to obtain as accurate a velocity as possible to ensure accur...

AI Technical Summary

Problems solved by technology

[0004] 1) The velocity spectrum is generally an equidistant scan. When the shape of the substrate changes rapidly, it is difficult for the discrete velocity spectrum to pick up the velocity at the lowest point, so the interpolated velocity cannot accurately reflect the change of the substrate shape;

[0005] 2) The velocity spectrum picks up the stacking velocity, and it is necessary to convert the stacking velocity into layer velocity during imaging. Since the current conversion formulas are mostly based on the assumption of horizontal layered media, and for places with complex deep structures, this conversion often has deviations. Thereby affecting the imaging effect;

[0006] 3) The middle and deep parts are often seriously affected by multiple waves, which makes it difficult to pick up the speed. If the speed picked up is not accurate, it may damage the effective signal during the multiple wave removal process, thereby affecting imag

Images