Software Development And Application Of Model Combination Based On Formation Component Analysis

With the development of society, the imbalance between supply and demand of energy consumption has become increasingly prominent. The importance of oil as an energy has become more notable, while lots of complex reservoirs of oil and gas reserves in the proportion of the total reserves and with the decrease efficiency in oil and gas exploration of the development of conventional reservoirs mining, the logging interpretation and evaluation technology for complex reservoir.The mineral in complex reservoir have become extremely complex duo to specific geological conditions. It may contain a variety of minerals:limestone, dolomite, sandstone, anhydrite, coal, rock salt, pyrite, gypsum and igneous. Because of the physical characteristics of partial skeleton component is very close, the conventional logging methods can’t effectively distinguish the component. The porosity and permeability model of complex reservoir is so difficult to establish that it’s difficult to achieve good results and provide accurate guidance for complex reservoir exploitment. The traditional logging interpretation method and conventional logging interpretation program usually can only use limited logging data. Fixed conventional logging interpretation model leads to conventional logging interpretation program can calculate limited number of formation component and the component is definite. Such as:POR program is designed for sand shale logging interpretation, CLASS program utilizes W-S model to evaluate the sand shale, CRA procedures for carbonatite reservoir logging interpretation.To improve the accuracy of complex reservoir interpretation, we need to utilize effectively logging data of complex reservoir, including core analysis data, logging data, well test data, and establish an appropriate physical model with reasonable simplification of the formation component in order to establish the corresponding equations based on the response characteristics of the simplified model and the logging tool. With the physical constraints and area constraints of the formation of the components, it can provide an effective way of logging interpretation of evaluate complex reservoirs based on the geophysics generalized inverse theory to strike the best interpretation of the results meet the ground conditions. For complex reservoir single model which contain a variety of minerals may not meet the needs of actual formation, the well logging interpretation may be not accurate. In order to improve the interpretation of the complex reservoir which contain lots of minerals, combination model can be adopted in the process of well logging. Model combination is to combine different physical models in an appropriate form with weighted average. The most important thing is how to get the weight coefficients.Through study of the formation component analysis procedures and the study of calculation method of the theoretical curve, this paper analyze the impact of error of the theoretical curve and the actual curve for the results and study the factors that would affect the combination results when composition process has been done. In order to eliminate the effects of different magnitude of the logging data, I have normalized the error between the theoretical curve and the measured curve and give different weights to the porosity curves to eliminate the impact of logging tools and logging curves quality.This paper identified two ways of combinations:model error method and given weight coefficient method. While the model error method establish weights based on the error between the theoretical curve and the measured curve, the number of curves and the number of components, the given weight coefficient method establish weights based on the analysis of the core data and the logging interpretation experience of that region. With the study of programming software and application platform, VC6.0 is chosen to develop the combination application and complete software running stability tests. This paper analysis the effect of the well data processing in different reservoir by processing the well logging data in order to test the combination in different depths and lithology of the well. The processing well logging data indicate that the combination of model component works well.