US 11,899,157 B2 · Well logging tool and interpretation framework that employs a system of artificial neural networks for quantifying mud and formation electromagnetic properties

Abstract

Methods and systems are provided that predict electromagnetic properties of drilling mud and a formation, which involve a logging tool that measures current injected into a measurement zone adjacent a sensor electrode at multiple frequencies. The measured currents at the multiple frequencies are processed to determine complex impedances for the sensor electrode at the multiple frequencies. The complex impedances are used to generate input data, which is supplied to a system of artificial neural networks (ANNs) that is configured to predict and output electromagnetic properties of the drilling mud and the formation within the measurement zone and possibly tool standoff based on the input data. The system of ANNs can employ a cascaded architecture of multiple ANNs. The electromagnetic properties or tool standoff predicted by the system of ANNs can be used to construct a borehole image over varying azimuth and depth.

Claims21

Dependent claims

A method of predicting electromagnetic properties of drilling mud and a formation, the method comprising:

configuring a logging tool to i) apply an alternating voltage of multiple frequencies to a sensor electrode that injects current into a measurement zone disposed adjacent the sensor electrode, wherein the measurement zone includes the drilling mud and the formation, and ii) measure values of the current injected into the measurement zone at the multiple frequencies;
processing the measured values of the current at the multiple frequencies to determine complex impedances for the sensor electrode at the multiple frequencies;
generating input data based on the complex impedances for the sensor electrode at the multiple frequencies;
supplying the input data to a system of artificial neural networks (ANNs) that is configured to predict and output the electromagnetic properties of the drilling mud and the formation within the measurement zone based on the input data, wherein the system of ANNs employs a cascaded architecture of multiple ANNs;
and
generating a borehole image over varying azimuth and depth using the electromagnetic properties.

3 more elements

A system for predicting electromagnetic properties of drilling mud and a formation, the system comprising at least one processor that, when executing program instructions stored in memory, is configured to:

obtain measurements of current injected into a measurement zone adjacent a sensor electrode at multiple frequencies, wherein the measurement zone includes the drilling mud and the formation;
process the measurements of the current at the multiple frequencies to determine complex impedances for the sensor electrode at the multiple frequencies;
generate input data based on the complex impedances for the sensor electrode at the multiple frequencies;
and
supply the input data to a system of artificial neural networks (ANNs) that is configured to predict and output electromagnetic properties of the drilling mud and the formation within the measurement zone based on the input data, wherein the system of ANNs employs a cascaded architecture of multiple ANNs and
generate a borehole image over varying azimuth and depth using the electromagnetic properties.

3 more elements

Dependencies are inferred from the claim text.

Well logging tool and interpretation framework that employs a system of artificial neural networks for quantifying mud and formation electromagnetic properties

Life of this patent

Well logging tool and interpretation framework that employs a system of artificial neural networks for quantifying mud and formation electromagnetic properties

Life of this patent

Abstract

Claims21