Thin layer thickness prediction method with combination of real drilling wells and virtual wells under rare well condition

Abstract

The invention relates to a thin layer thickness prediction method with combination of real drilling wells and virtual wells under a rare well condition. The technical scheme is as follows: a geologic model is established according to drilling and logging data of existing real drilling wells and field outcrop test analysis data; forward modeling of the established model is carried out, analysis of a causal relationship of the thin layer thickness and seismic attribution change is carried out through the forward modeling result, and wavelet fine calibration is employed to match simulated earthquake record and practical earthquake recode in virtual drilling wells and real drilling wells; based on the established geologic model and the forward modeling earthquake record after matching, different thin layer thicknesses in the model and corresponding seismic attributions in the simulated earthquake record are extracted, a seismic attribution sample set is established, and permutation and combination of the sample set of the virtual drilling wells and the sample set of the real drilling wells are carried out. The above technical scheme is employed, the method increasing effective sample point number and lowering earthquake thin layer prediction multi-solution obviously under a condition that drilling wells are few in an exploration early stage is provided.

Description

technical field [0001] The invention relates to energy exploration, in particular to a method for predicting the thickness of a thin layer by combining actual drilling and virtual wells under rare well conditions. Background technique [0002] Due to the shortage of energy, the exploitation of underground energy (ie, oil, natural gas and shale gas) is a more important research direction of current scientific research. As we all know, there is a large amount of energy in underground reserves. However, its distribution is wide and uneven. Before mining, it needs to be more accurately explored and studied. The exploration is mainly carried out by means of drilling and geophysics. However, after decades of development, the current oil and gas exploration has shifted to the stage of fine exploration, which puts forward higher requirements for the prediction accuracy of thin oil and gas reservoirs. Exploration potential, that is, whether the block has relatively abundant energy a...

AI Technical Summary

Problems solved by technology

[0003] However, thin layer thickness prediction has always been one of the recognized difficulties, and too many wells in this area will cost a lot of money, making it unaffordable for scientific research and construction units.

The traditional prediction method is to analyze and predict the drilling data when a small number of wells are drilled. Due to the small number of wells, the effective sample points for analysis are scarce, and the prediction results are difficult to achieve accuracy. The evaluation and mining cannot achieve the expected results, and at the same time, it will waste more manpower and material resources

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