A reservoir water production rate calculation method based on an apparent oil layer resistivity curve

Abstract

The invention discloses a reservoir water production rate calculation method based on an apparent oil layer resistivity curve. The method comprises the following steps of firstly, carrying out reservoir classification by utilizing a conventional logging curve; then constructing an apparent oil layer resistivity model on the basis of reservoir classification, and calculating an apparent oil layer resistivity curve; and finally, comparing the apparent oil layer resistivity curve with the deep detection resistivity curve, qualitatively judging the reservoir fluid property, and quantitatively calculating the water production rate of the reservoir according to the logarithm normalization difference value of the apparent oil layer resistivity curve and the deep detection resistivity curve. According to the method, the fluid property of the reservoir is simply and accurately judged, the water production rate of the reservoir is accurately calculated, a reference basis can be provided for development of a water flooded layer, and a guidance basis is provided for adjustment of middle and later development schemes of an oil field.

Description

Technical field [0001] The invention belongs to the technical field of data analysis of oil reservoir engineering, and specifically relates to a method for calculating reservoir water production rate based on apparent oil layer resistivity curve. Background technique [0002] Whether for oil fields in the exploration stage or the development stage, the identification of reservoir fluid properties and the calculation of water production rate are very important tasks. At present, the fluid property discrimination method can be divided into the discrimination method based on special logging data and the discrimination method based on conventional logging data. Although the fluid property discrimination method based on special logging data (NMR logging, modular formation tester, etc.) is relatively accurate, the special logging construction is expensive, and generally only a few wells are selected for measurement. Therefore, most wells rely on conventional logging for fluid property...

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Problems solved by technology

However, these methods have some disadvantages: for example, the absolute value method of resistivity and the difference method of deep and shallow resistivity do not consider the influence of factors such as reservoir pore structure and mud value content; the acoustic wave-neutron curve overlapping method can only judge natural gas and water; The porosity-water saturation crossplot method needs to pre-calculate the porosity and water saturation parameters, and the error is transmitted step by step, resulting in low discrimination accuracy; the neural network method, support vector machine method and other methods are often cumbersome to operate, and the training samples extremely demanding

However, this method also has the problem of low calculation accuracy caused by error transmission step by step. Therefore, it is necessary to develop other more accurate, intuitive, and easy-to-operate fluid property discrimination methods based on conventional logging data.

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