# US 11,307,323 B2 · Methods and systems to analyze bed boundary detection

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- Number: US 11,307,323 B2
- Document ID: US11307323B2
- Status: Granted
- Kind: B2
- Application number: 15/764,614
- Filed: 2016-09-26
- Published: 2018-10-11
- Granted: 2022-04-19
- Earliest claimed: 2015-09-30
- Assignees: Schlumberger Technology Corporation
- Applicants: Schlumberger Technology Corporation
- Inventors: Helen Xiaoyan Zhong; Steve F. Crary; Ettore Mirto; Christophe Dupuis; Weixin Dong; Mark T. Frey
- Web page: https://patentgrep.com/patent/US11307323B2

## CPC

- G01V 3/38: Processing data, e.g. for analysis, for interpretation, for correction
- E21B 47/09: Locating or determining the position of objects in boreholes or wells {, e.g. the position of an extending arm}; Identifying the free or blocked portions of pipes
- 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 3/26: operating with magnetic or electric fields produced or modified either by the surrounding earth formation or by the detecting device (with electromagnetic waves G01V3/30)
- G01V 3/30: operating with electromagnetic waves
- 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

## Abstract

Methods capable of determining a depth of investigation of a logging tool can include generating an error distribution model for a logging tool. The methods can also include defining a detection threshold above which a measured signal from a measurement channel of the logging tool can be considered reliable based on output from the error distribution model, and generating a simulated formation model to determine the depth of investigation. The depth of investigation can be biased by the detection threshold.

## Claims

### Claim 1

A method to determine a depth of investigation, comprising:
generating an error distribution model for a logging tool;
generating, for each of a plurality of measurement channels of the logging tool, a corresponding standard deviation distribution from the error distribution model with application of noise and systematic errors to the error distribution model, wherein the corresponding standard deviation distribution spans a range of formation resistivities;
defining, for each of the plurality of measurement channels, a corresponding resistivity dependent detection threshold above which a corresponding measurement channel signal considered reliable based on the corresponding standard deviation distribution;
generating, for each of the plurality of measurement channels, a corresponding simulated formation model to determine depth of investigation, the depth of investigation being biased by the corresponding resistivity dependent detection threshold; and
generating, for the plurality of measurement channels, a multiple channel detection range map for detection of a shoulder using the depth of investigation for each of the plurality of measurement channels, the multiple channel detection range map providing a gauge of sensitivity corresponding to resistivity contrasts between a formation and the shoulder.

### Claim 2 (depends on 1)

The method of claim 1, wherein the generating comprises generating detection range maps for each of the plurality of measurement channels.

### Claim 3 (depends on 2)

The method of claim 2, wherein the generating comprises combining the detection range maps to generate the multiple channel detection range map as a single detection range map.

### Claim 4 (depends on 3)

The method of claim 3, wherein the combining includes determining a maximum depth of investigation for each of the plurality of measurement channels.

### Claim 5

A method to determine distances to a bed boundary of an earth formation, comprising:
acquiring input data for a logging tool;
constructing a forward model based on the input data;
applying a plurality of errors to the forward model;
generating inverted maps corresponding to horizontal resistivities of the earth formation by applying an inversion technique to the forward model to predict distances to the bed boundary, the applying a plurality of errors to the forward model generating corresponding inverted maps;
defining a threshold to compare the predicted distances to the bed boundary with a true formation model which provides true distances to the bed boundary, wherein the threshold is defined using a relative confidence level being tested, a top resistivity and a bottom resistivity, wherein the threshold, RThreshold, is defined by equation
1
R
Treshold
=
level
R
t
⁢
o
⁢
p
-
1
-
level
R
b
⁢
o
⁢
t
⁢
t
⁢
o
⁢
m
where the level is the relative confidence level being tested, Rtop is the top resistivity and Rbottom is the bottom resistivity; and
displaying results that exceed the threshold, wherein the displaying the results that exceed the threshold includes displaying results that correspond to the distances to the bed boundary and a percentage of realizations.

### Claim 6 (depends on 5)

The method of claim 5, wherein the results that exceed the threshold includes at least one of:
first data points where the horizontal resistivities of the inverted maps exceed the threshold;
three consecutive data points where the horizontal resistivities of the inverted maps exceed the threshold; and
three consecutive data points where the horizontal resistivities of the inverted maps exceed the threshold within a predefined range.

### Claim 7 (depends on 5)

The method of claim 5, wherein the defining a threshold to compare the predicted distances to the bed boundary with a true formation model which provides a true distance to the bed boundary includes applying a color scale to images of the inverted maps.

### Claim 8 (depends on 5)

The method of claim 5, wherein the applying a plurality of errors to the forward model includes randomly generating at least one of noise and systematic errors.

### Claim 9 (depends on 5)

The method of claim 5, wherein a lower relative confidence level improves sensitivity of the results and wherein a higher relative confidence level makes the results less sensitive and more robust.

### Claim 10

A system comprising:
one or more processors;
memory operatively coupled to the one or more processors; and
processor-executable instructions stored in the memory and executable by at least one of the processors to instruct the system to:
construct a forward model based on the logging tool data;
apply a plurality of errors to the forward model;
generate inverted maps corresponding to horizontal resistivities of the earth formation by applying an inversion technique to the forward model to predict distances to the bed boundary, the applying a plurality of errors to the forward model generating corresponding inverted maps;
define a threshold to compare the predicted distances to the bed boundary with a true formation model which provides true distances to the bed boundary, wherein the threshold is defined using a relative confidence level being tested, a top resistivity and a bottom resistivity, wherein the threshold, RThreshold, is defined by equation
1
R
Threshold
=
level
R
top
-
1
-
level
R
bottom
where the level is the relative confidence level being tested, Rtop is the top resistivity and Rbottom is the bottom resistivity; and
display results that exceed the threshold, wherein the display the results that exceed the threshold includes display of results that correspond to the distances to the bed boundary and a percentage of realizations.

### Claim 11 (depends on 10)

The system of claim 10, wherein the results that exceed the threshold comprises at least one of:
first data points where the horizontal resistivities of the inverted maps exceed the threshold;
three consecutive data points where the horizontal resistivities of the inverted maps exceed the threshold; and
three consecutive data points where the horizontal resistivities of the inverted maps exceed the threshold within a predefined range.

### Claim 12 (depends on 10)

The system of claim 10, wherein define a threshold to compare the predicted distances to the bed boundary with a true formation model which provides a true distance to the bed boundary comprises applying a color scale to images of the inverted maps.

### Claim 13 (depends on 10)

The system of claim 10, wherein a lower relative confidence level improves sensitivity of the results and wherein a higher relative confidence level makes the results less sensitive and more robust.