Pattern Recognition Adaptive Full Waveform Inversion Method

Abstract

The invention discloses a pattern recognition self-adaptive full waveform inversion method, which adopts the following steps: Step 1, complete the following steps for each shot set record: 1-1 Calculate the forward propagation wave field at each moment; 1-2 Calculate the accompanying source and back-propagate it to obtain the back-propagation data; 1-3 Calculate the cross-correlation between the back-propagation wave field and the forward propagation wave field to obtain the gradient of a single shot; Step 2, obtain the gradient superposition of all shots to obtain the model The global gradient of the space; step 3, obtain the modification amount of the velocity model through the steepest descent method or the local inversion algorithm, and then obtain the optimized velocity model. The present invention does not have the restriction that only the low-frequency components of seismic data can be used, and can use the medium-frequency and high-frequency components of seismic records, such as frequency components within the main frequency range, and there is no cycle jump in conventional full waveform inversion technology that leads to wrong solutions Defects.

Description

technical field [0001] The invention relates to a pattern recognition self-adaptive full waveform inversion method, which belongs to the application field of oil and gas exploration. Background technique [0002] Oil and gas resources are not only of great significance to the country's economy but also to the country's strategic significance. my country is a country with a large demand for energy, and spends a lot of money to buy foreign oil every year. In addition to causing huge economic losses to the country, it also poses a huge challenge to the country's energy strategy. How to find oil and gas resources buried in the depth of thousands of meters to tens of thousands of meters underground is a huge problem and goal that major oil companies in the world are currently facing. It requires first to obtain a three-dimensional image of the underground. This process is commonly referred to as geophysical exploration, and then judges whether there are oil and gas resources und...

AI Technical Summary

Problems solved by technology

How to obtain a high-precision underground velocity model has always been the goal of people's efforts, but due to the high difficulty of its technology, there has been no breakthrough in this field

[0004] With the deepening of geophysical exploration, people are trying to study how to obtain a high-precision velocity model. For this reason, the technology of full waveform inversion has been proposed. This technology has achieved certain results to a certain extent, but this technology can only use seismic The recorded low-frequency components are used to invert the subsurface velocity model, otherwise there will be a very troublesome problem of cycle jump, but unfortunately, the low-frequency components of seismic records are often greatly affected by interference waves, and the signal-to-noise ratio is relatively low, such as Interference waves such as surface waves or surges generated by sea waves appear in the form of strong energy and low frequency, which affect the low frequency components of seismic signals, while conventional full waveform inversion technology can only use low frequency components of seismic waves, which is obviously not what we want of

In addition, the low-frequency component of the seismic wave cannot obtain the high-frequency component of the velocity model, that is to say, the detailed changes of the velocity model cannot be obtained, which also restricts the accuracy of the velocity model

Images