# US 11,307,322 B2 · Mixed inversion using a coarse layer model

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 11,307,322 B2
- Document ID: US11307322B2
- Status: Granted
- Kind: B2
- Application number: 16/325,998
- Filed: 2016-09-19
- Published: 2021-02-11
- Granted: 2022-04-19
- Earliest claimed: 2016-09-19
- Assignees: Halliburton Energy Services, Inc.
- Applicants: Halliburton Energy Services, Inc.
- Inventors: Yumei Tang; Burkay Donderici
- Web page: https://patentgrep.com/patent/US11307322B2

## CPC

- G01V 3/28: using induction coils
- E21B 49/00: Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
- G01V 3/38: Processing data, e.g. for analysis, for interpretation, for correction
- G06F 30/20: Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30)
- E21B 2200/20: Computer models or simulations, e.g. for reservoirs under production, drill bits
- G06F 2111/10: Numerical modelling
- G01V: GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS (means for indicating the location of accidentally buried, e.g. snow-buried, persons A63B29/02)
- E21B: EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)

## Abstract

A look-ahead logging method includes obtaining an initial resistivity log. The method further includes deriving an initial formation model based on the initial resistivity log. The method further includes estimating deep resistivity measurements from the initial formation model and deriving a reduced-complexity formation model from the estimated deep resistivity measurements. The method further includes collecting actual resistivity measurements and inverting the actual resistivity measurements, using the reduced-complexity formation model, to obtain look-ahead or look-around parameter values. The method further includes displaying the look-ahead or look-around parameter values or storing the look-ahead or look-around parameter values on a non-transient information storage medium.

## Claims

### Claim 1

A look-ahead logging method that comprises:
obtaining an initial resistivity log from a logging tool conveyed along a borehole;
deriving an initial formation model based at least in part on the initial resistivity log;
estimating deep resistivity measurements from the initial formation model, the deep resistivity measurements associated with a measurement range greater than that of the initial resistivity log;
deriving a reduced-complexity formation model from the estimated deep resistivity measurements, wherein the reduced-complexity formation model includes a lower number of coarser formation layers compared to the a higher number of finer formation lavers included in the initial formation model;
collecting actual resistivity measurements with a range greater than that of the initial resistivity log;
inverting the actual resistivity measurements to obtain look-ahead or look-around parameter values, said inverting using the reduced-complexity formation model;
and
displaying the look-ahead or look-around parameter values or storing the look-ahead or look-around parameter values on a non-transient information storage medium.

### Claim 2 (depends on 1)

The method of claim 1, wherein deriving the reduced-complexity formation model comprises replacing the higher number of finer formation layers in the initial formation model with the lower number of coarser formation layers.

### Claim 3 (depends on 1)

The method of claim 1, wherein the reduced-complexity formation model comprises look-ahead layers or look-around layers.

### Claim 4 (depends on 1)

The method of claim 1, wherein the reduced-complexity formation model comprises layers with anisotropic resistivity, and the initial formation model comprises layers with isotropic resistivity.

### Claim 5 (depends on 1)

The method of claim 1, wherein the reduced-complexity formation model comprises layers with anisotropic resistivity, and initial formation model comprises layers with anisotropic resistivity.

### Claim 6 (depends on 1)

The method of claim 1, wherein estimating deep resistivity measurements comprises performing a forward modeling process.

### Claim 7 (depends on 1)

The method of claim 1, further comprising using the look-ahead or look-around parameter values for geosteering decisions.

### Claim 8

A system for creating an inverted deep-resistivity formation model comprising:
a transmitter;
a first receiver antenna at a first axial distance from the transmitter, wherein the first receiver antenna collects real shallow-resistivity measurements;
a second receiver antenna at a second axial distance from the transmitter, wherein the second receiver antenna collects real deep-resistivity measurements and wherein the second axial distance is greater than the first axial distance; and
one or more processors coupled to the first and second receiver antennas, wherein the one or more processors:
obtain an initial resistivity log;
derive an initial formation model based at least in part on the initial resistivity log;
estimate deep resistivity measurements from the initial formation model, the deep resistivity measurements associated with a measurement range greater than that of the initial resistivity log;
derive a reduced-complexity formation model from the estimated deep resistivity measurements, wherein the reduced-complexity formation model includes a lower number of coarser formation layers compared to the a higher number of finer formation layers included in the initial formation model;
collect actual resistivity measurements with a range greater than that of the initial resistivity log; and
invert the actual resistivity measurements to obtain look-ahead or look-around parameter values, said inverting using the reduced-complexity formation model.

### Claim 9 (depends on 8)

The system of claim 8, wherein deriving the reduced-complexity formation model causes the one or more processors to replace the higher number of finer formation layers in the initial formation model with the lower number of coarser formation layers.

### Claim 10 (depends on 8)

The system of claim 8, wherein the reduced-complexity formation model comprises look-ahead layers or look-around layers.

### Claim 11 (depends on 8)

The system of claim 8, wherein estimating deep resistivity measurements causes the one or more processors to perform a forward modeling process.

### Claim 12 (depends on 8)

The system of claim 8, wherein the one or more processors are further caused to use the look-ahead parameter values for geosteering decisions.

### Claim 13 (depends on 8)

The system of claim 8, wherein a resistivity tool comprises the transmitter, first receiver antenna, and second receiver antenna.

### Claim 14 (depends on 13)

The system of claim 13, wherein the resistivity tool comprises the one or more processors.

### Claim 15 (depends on 13)

The system of claim 13, wherein the one or more processors are distributed among a downhole resistivity tool and a computer located at the surface.

### Claim 16

A method of creating an inverted deep-resistivity formation model comprising:
synthesizing deep-resistivity measurements based on a shallow-resistivity model created from real shallow-resistivity measurements;
creating an equivalent deep-resistivity formation model based on the synthesized deep-resistivity measurements;
creating an augmented deep-resistivity formation model by adding unknown formation layers to the equivalent deep-resistivity model;
creating an inverted deep-resistivity formation model by performing an inversion on the augmented deep-resistivity formation model; and
displaying at least a portion of the inverted deep-resistivity formation model.

### Claim 17 (depends on 16)

The method of claim 16, wherein creating the equivalent deep-resistivity formation model comprises replacing a higher number of finer formation layers in the shallow-resistivity model with a lower number of coarser formation layers.

### Claim 18 (depends on 16)

The method of claim 16, wherein synthesizing the deep-resistivity measurements comprises performing a forward modeling process.

### Claim 19 (depends on 16)

The method of claim 16, wherein the inverted deep-resistivity formation model is based on real deep-resistivity measurements.

### Claim 20 (depends on 19)

The method of claim 19, wherein the inverted deep-resistivity formation model is based on the real shallow-resistivity measurements.