# US 10,481,292 B2 · Statistical methods for assessing downhole casing integrity and predicting casing leaks

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- Number: US 10,481,292 B2
- Document ID: US10481292B2
- Status: Granted
- Kind: B2
- Application number: 16/119,717
- Filed: 2018-08-31
- Published: 2019-02-28
- Granted: 2019-11-19
- Earliest claimed: 2015-07-09
- Assignees: Saudi Arabian Oil Company
- Applicants: Saudi Arabian Oil Company
- Inventors: Abdulrahman Mishkhes; Mohammed D. Al-Ajmi; Mubarak J. Al-Shammari
- Web page: https://patentgrep.com/patent/US10481292B2

## CPC

- G01V 3/38: Processing data, e.g. for analysis, for interpretation, for correction
- E21B 47/006: {Detection of corrosion or deposition of substances}
- G01N 17/04: Corrosion probes
- G01V 3/18: specially adapted for well-logging
- 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
- G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q)

## Abstract

The present disclosure describes methods and systems, including computer-implemented methods, computer program products, and computer systems, for predicting casing leaks. One computer-implemented method includes obtaining raw electromagnetic (EM) corrosion data for a hotspot, wherein the raw EM corrosion data includes a metal thickness loss value for the hotspot; determining a corrosion parameter based on the raw EM corrosion data; generating a probability distribution curve for the corrosion parameter; generating a corrosion severity classification matrix based on the probability distribution curve, wherein the corrosion severity classification matrix includes a plurality of corrosion severity classes and cutoff values for each of the plurality of corrosion severity classes; and assigning the hotspot into one of the plurality of corrosion severity classes based on the corrosion severity classification matrix and the corrosion parameter of the hotspot.

## Claims

### Claim 1

A system for predicting downhole casing leaks of hotspots, comprising:
a memory; and
at least one hardware processor interoperably coupled with the memory and configured to:
obtain, from corrosion logs generated by an electromagnetic (EM) logging tool, raw EM corrosion data for a hotspot, wherein the raw EM corrosion data includes a metal thickness loss value for the hotspot;
determine a corrosion parameter based on the raw EM corrosion data, wherein the corrosion parameter includes a corrosion rate that is calculated based on an original thickness value, a remaining thickness value, and a number of years;
generate a probability distribution curve for the corrosion parameter;
generate a corrosion severity classification matrix based on the probability distribution curve, wherein the corrosion severity classification matrix includes a plurality of corrosion severity classes and cutoff values for each of the plurality of corrosion severity classes;
assign the hotspot into one of the plurality of corrosion severity classes based on a comparison of the cutoff values for the plurality of corrosion severity classes in the corrosion severity classification matrix and the corrosion parameter of the hotspot; and
generate a service alert for the hotspot based on the assigned corrosion severity class.

### Claim 2 (depends on 1)

The system of claim 1, wherein the generation of the probability distribution curve comprises:
determining whether the hotspot is a leaking hotspot or a non-leaking hotspot;
if the hotspot is a leaking hotspot, generating a probability distribution curve for the corrosion parameter based on corrosion parameters for leaking hotspots; and
if the hotspot is a non-leaking hotspot, generating a probability distribution curve for the corrosion parameter based on corrosion parameters for non-leaking hotspots.

### Claim 3 (depends on 1)

The system of claim 1, wherein the raw EM corrosion data includes metal loss values for a plurality of strings, and the corrosion parameter includes an average remaining barrier that is calculated based on a nominal thickness value for each of the plurality of strings, and a thickness loss value for each of the plurality of strings.

### Claim 4 (depends on 1)

The system of claim 1, wherein the generation of the probability distribution curve for the corrosion parameter comprises:
calculating a mean value and a standard deviation value of the corrosion parameter for leaking hotspots;
calculating a mean value and a standard deviation value of the corrosion parameter for non-leaking hotspots;
generating a probability distribution function of the leaking hotspots based on the mean value and the standard deviation value of the corrosion parameter for leaking hotspots; and
generating a probability distribution function of the non-leaking hotspots based on the mean value and the standard deviation value of the corrosion parameter for non-leaking hotspots.

### Claim 5 (depends on 1)

The system of claim 1, wherein the cutoff values for each of the plurality of corrosion severity classes is determined based on a mean value of the corrosion parameter for leaking hotspots, a standard deviation value of the corrosion parameter for leaking hotspots, a mean value of the corrosion parameter for non-leaking hotspots, and a standard deviation value of the corrosion parameter for non-leaking hotspots.

### Claim 6 (depends on 1)

The system of claim 1, wherein each of the plurality of corrosion severity classes is associated with a logging frequency for the respective corrosion severity class.