FIELD: geophysics.
SUBSTANCE: invention relates to the field of exploration geophysics and can be used for assessment of potential of hydrocarbon deposits. According to the electromagnetic probing data, a one-dimensional profile of the specific electric resistance to the predetermined depth is plotted at the forecast point. Method includes interpolating porosity logging and electric logging logs in available wells as well as resistivity obtained by inversion of electromagnetic probing data in its vicinity to the same depth to the bottomhole. At the second stage, the first artificial neuronet is trained on compliance of specific electric resistance obtained as a result of inversion of electromagnetic probing data at the input of the first neural network and data of electric logging at its output. Using the trained first artificial neural network, the forecast of electromagnetic logging of resistance in the forecast point from the surface to the target depth is made based on values of specific resistance obtained as a result of inversion of electromagnetic probing data in the vicinity of the well. At the third stage, the second artificial neuron network is trained on compliance of values of electrical resistivity of electric logging at its input and porosity logging at its output. Using the second trained artificial neural network, forecast of porosity in point of forecast from surface to target depth is made by values of electromagnetic resistance logging, constructed at the first stage.
EFFECT: technical result consists in constructing a prediction profile of porosity in a given point at depths from surface to target depth.
3 cl, 1 tbl, 6 dwg
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Authors
Dates
2020-03-25—Published
2019-05-28—Filed