Method and device for performing fitting inversion by utilizing plurality of pieces of data to realize complex lithologic interpretation

Abstract

The invention discloses a method and a device for performing fitting inversion by utilizing a plurality of pieces of data to realize complex lithologic interpretation. The method comprises the following steps of dividing a reservoir into fluid components, muddy components and rock matrix components according to the geological condition of a research work area; setting a fluid component response characteristic value and a muddy component response characteristic value; determining the types and the number of the rock matrix components in the research work area and a rock matrix component response characteristic value according to logging data by utilizing methods of oilfield on-site coring, geologic description, physical property analysis and laboratory thin section authentication; acquiring a conventional logging response value and the element content of the stratum of the research work area by utilizing a logging instrument; establishing a logging response equation set by combining a conventional logging curve and an elemental capture spectroscopy logging curve; performing joint inversion to obtain the optimal relative volumes of the fluid components, the muddy components and the rock matrix components in the stratum of the research work area by utilizing the logging response equation set and householder transformation and conjugate gradient optimization algorithms, and drawing lithologic analysis results.

Description

technical field [0001] The invention is aimed at the analysis of complex lithology reservoirs, especially a complex lithology interpretation method and device using multiple data fitting and inversion. Background technique [0002] As a main method for qualitative and quantitative evaluation of reservoirs, logging technology runs through all stages of oil and gas exploration and development, and plays an important role in the evaluation of clastic rock reservoirs. With the increasingly complex exploration objects, logging technology is becoming more and more More and more attention has been paid, but there are still many problems and challenges. The evaluation of volcanic rock reservoirs is the focus of the description of volcanic rock reservoirs, and the interpretation of volcanic rock lithology is the basis of volcanic rock reservoir evaluation. Inaccurate lithological interpretation will directly lead to the loss of oil and gas layers. Therefore, accurate lithological i...

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Problems solved by technology

[0003] Most of the previous researchers only used conventional logging data and seismic data, etc., and adopted parameter crossplot method, imaging logging identification method, neural network method, correspondence analysis identification method, dipole acoustic logging, rock strength parameter identification method, Seismic method and other methods, the identification result is a simple lithology profile, which mainly stays at the qualitative level, and cannot provide accurate lithology profile data for fine exploration and development, especially in the oil and gas exploration of volcanic rocks, due to the lithology of the logging response The influence of lithology often exceeds the influence of reservoir fluid, so the fine interpretation of lithological composition will be the key to the success of exploration

Elemental Capture Spectroscopy (ECS logging for short) can measure the information of various elements that make up formation rocks, which provides a possibility to explain the lithology of volcanic rocks from the perspective of chemical composition, but due to the closure of oxides The model is not easy to determine, making it difficult to quickly master the technology and difficult to promote and apply it

On the other hand, in the previous studies, a lot of complicated work had to be done before the application of element capture spectroscopy logging data, such as oxide closure model, conversion of original value to relative content, etc., and these calculations are not easy to master, and the regions are different. The model parameters are also very different, and it is impossible to form an easy-to-operate and effective quantitative interpretation method for volcanic rock lithology with conventional logging data

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