Resistivity inversion initial value selection method based on array lateral logging data

Abstract

The invention discloses a resistivity inversion initial value selection method based on array lateral logging data. The method comprises steps that forward calculation is carried out based on a radialstep stratum model, resistivity amplitude difference coefficients S1, S2, S3, S4, S5 and S6 are defined, four basic logging curves MLR1a, MLR2a, MLR3a and MLR4a corresponding to the radial step stratum model are obtained, and a change chart of resistivity amplitude difference coefficients along with the radius of a flushing zone is established; the quantitative relation between an initial value rxocz of the radius of the flushing zone and the resistivity amplitude difference coefficients is established through linear regression based on the change chart of the resistivity amplitude differencecoefficients along with the radius of the flushing zone; the MLR4a is utilized as a stratum resistivity initial value Rtcz, and a flushing zone resistivity initial value Rxocz is obtained based on pseudo-geometric factor definition. The resistivity inversion initial value selection method based on the array lateral logging data is advantaged in that deviation between the initial value and a realvalue can be effectively reduced without supplementing other logging data, and resistivity logging inversion precision and the speed can be improved.

Description

technical field [0001] The invention relates to the technical field of logging evaluation in the exploration and development of oil and gas resources, in particular to a method for selecting an initial value of resistivity inversion based on array lateral logging data. Background technique [0002] Reservoir resistivity data is of great use in oil layer evaluation. Resistivity can not only be used to qualitatively identify oil and gas layers (generally, oil layers show high resistance characteristics), but also can be used to quantitatively calculate oil saturation (using the formulas of Archie or Indonesia, etc. ). A variety of resistivity logging methods have been widely used in oilfields, such as dual laterologging, dual induction logging, array laterologging, array induction logging, electrical imaging logging, etc. Compared with traditional dual-lateral lateral and dual-induction logging tools, array resistivity logging tools can provide multiple apparent resistivity c...

AI Technical Summary

Problems solved by technology

This inversion algorithm has a very fast convergence speed, which is beneficial to the real-time inversion of logging data, but the disadvantages of this type of algorithm are also exposed in the actual application process, that is, the inversion result is greatly affected by the initial value, if the initial value is set Unreasonable (far away from the true value), it is difficult to accurately invert the true resistivity value of the formation, which seriously affects the inversion accuracy

In order to solve the problems existing in the Marquette algorithm, some scholars have introduced global optimization algorithms such as simulated annealing method, genetic algorithm, artificial neural network algorithm, immune algorithm, differential evolution algorithm, and particle swarm optimization into the inversion processing of electrical logging data. , this type of algorithm has a strong global search ability, which can effectively improve the inversion accuracy, but the convergence speed is generally slow, and it is not suitable for the rapid processing of electrical logging data, and its use is limited. The Marquette algorithm is still the field array side The primary choice for real-time inversion of log data

Images