Patent ID: 11860325
Assignee: SAUDI ARABIAN OIL COMPANY
Field: Measurement (Instruments)
Classification: CPC G  H  E | IPC E  G

Claim 11:
12. A method for drilling a new well in a subterranean formation by training a multi-head Convolutional Neural Network (CNN) model to estimate a rock property away from a drilled well, the method comprising:
accessing synthetic seismic data in a training dataset used for training the multi-head CNN model;
accessing rock property log data associated with the drilled well;
training the multi-head CNN model to:
determine one or more relationships between the synthetic seismic data and the rock property log data; and
output an estimated rock property value for a formation zone away from the drilled well based on the one or more relationships between the synthetic seismic data and the rock property log data;

updating a drilling program for a production system based on the estimated rock property value; and
drilling the new well in the area of interest and according to the drilling program,
wherein the multi-head CNN model includes a plurality of heads and a plurality of layers,
wherein each head of the plurality of heads is an input channel that reads the acquired 3D seismic data at a different resolution per input channel, and
wherein each head includes a kernel of a different size in a one-dimensional (1D) convolution layer of the plurality of layers,
wherein a first layer of the plurality of layers receives the seismic traces as input,
wherein a second layer of the plurality of layers is the 1D convolution layer which scans the seismic traces, the second layer comprising sixty-four neurons, a kernel of a particular size, a stride of one, and a nonlinear activation function;
wherein a third layer of the plurality of layers performs a dropout procedure on one or more nodes of the multi-head CNN model at a drop rate of 0.3;
wherein a fourth layer of the plurality of layers performs a batch normalization and a concatenation of the output of the plurality of heads;
wherein a fifth layer of the plurality of layers is a densely-connected layer with one neuron; and
wherein a sixth layer of the plurality of layers outputs the estimated rock property value.