# US 11,898,552 B2 · Method and system for predicting failures of sucker rod pumps using scaled load ratios

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- Number: US 11,898,552 B2
- Document ID: US11898552B2
- Status: Granted
- Kind: B2
- Application number: 17/403,806
- Filed: 2021-08-16
- Published: 2023-02-23
- Granted: 2024-02-13
- Earliest claimed: 2021-08-16
- Assignees: SK Innovation Co., Ltd.; SK Earthon Co., Ltd.; Seoul National University R&Db Foundation
- Applicants: SK Innovation Co., Ltd.; SK Earthon Co., Ltd.; Seoul National University R&DB Foundation
- Inventors: Jongyoung Jun; Yeonjun Park; Ha Eun Kim; Hoonyoung Jeong; Byunggun Oh; Yeongju Kim
- Web page: https://patentgrep.com/patent/US11898552B2

## CPC

- F04B 51/00: Testing machines, pumps, or pumping installations
- E21B 47/008: Monitoring of down-hole pump systems, e.g. for the detection of "pumped-off" conditions
- E21B 47/009: Monitoring of walking-beam pump systems
- F04B 47/00: Pumps or pumping installations specially adapted for raising fluids from great depths, e.g. well pumps (by using positive or negative pressurised fluid medium acting directly on the liquid to be pumped F04F1/00)
- F04B 49/065: {and making use of computers}
- E21B 2200/20: Computer models or simulations, e.g. for reservoirs under production, drill bits
- F04B 2201/0202: Linear speed of the piston
- F04B 2201/121: Load on the sucker rod
- F04B: POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS (machines for liquids, or pumps, of rotary-piston or oscillating-piston type F04C; non-positive-displacement pumps F04D; pumping of fluid by direct contact of another fluid or by using inertia of fluid to be pumped F04F)
- E21B: EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS

## Abstract

A system and method for predicting failures of rod pumps using a scaled load ratio is configured to: optimize the size of a rolling window, the upper and lower bounds of the normal range of the scaled load ratio, an alert period, and an alert frequency ratio; receive data of a current maximum/minimum loads on a surface rod, and a current speed; remove outliers showing an abnormality; scale the current maximum/minimum loads on the surface rod using the maximum/minimum loads on the surface rod in normal operation; calculate a scaled load ratio; calculate the average of scaled load ratios in the rolling window; determine whether the average of scaled load ratios is in the normal range, and classify the values as normal and abnormal events; calculate the ratio of the abnormal events in the alert period, and generate an alert when the calculated ratio exceeds the alert frequency ratio; and monitor a pump state using the pump failure prediction system.

## Claims

### Claim 1

A method of predicting pump failures of rod pumps using a scaled load ratio, the method comprising:
optimizing a size of a rolling window, upper and lower bounds of a normal range of the scaled load ratio, an alert period, and an alert frequency ratio as optimal input values through an optimization module constituting software;
receiving data of a current maximum load on a surface rod, a current minimum load on the surface rod, and a current speed of a target oil well pump from a storage device by means of a processor of a pump failure prediction system;
removing outliers from the received data on the basis of an outlier removable reference set using an outlier removable module constituting the software that is executed by the processor to generate filtered data;
receiving data of maximum and minimum loads on the surface rod in normal operation from the storage device and scaling the maximum and minimum loads by means of the processor;
calculating scaled load ratios using a scaled load ratio calculation module constituting the software using the filtered data;
calculating an average of the scaled load ratios in the rolling window using a scaled load ratio through average value calculation module constituting the software by applying a rolling window method to remove noises of the scaled load ratios;
determining whether the average of the scaled load ratios is in the normal range, and classifying the scaled load ratios as normal events or abnormal events using a scaled load ratio-normal range determination and classification module constituting the software;
calculating a ratio of the abnormal events and generating an alert when the ratio of the abnormal events exceeds the alert frequency ratio using a failure data ratio calculation and alert generation module constituting the software; and
monitoring a pump state using the pump failure prediction system to accurately predict the pump failures using the scaled load ratios, a pump speed, a pump card, and a pump fillage.

### Claim 2 (depends on 1)

The method of claim 1, wherein the optimizing is performed when the size of the rolling window, the upper and lower bounds of the normal range of the scaled load ratio, the alert period, and the alert frequency ratio are initially set as the optimal input values, or is performed when a rod pump is reinstalled, repaired, or replaced.

### Claim 3 (depends on 1)

The method of claim 1, wherein the size of the rolling window, the upper and lower bounds of the normal range of the scaled load ratio, the alert period, and the alert frequency ratio that are the optimal input values set using the optimization module are stored in the storage device.

### Claim 4 (depends on 1)

The method of claim 1, wherein a Matthews Correlation Coefficient (MCC) that is an index for evaluating analysis performance is used in an objective function that is used for optimization during the optimizing, and the MCC is calculated by Equation 3,
MCC
=
TP
×
TN
-
FP
×
FN
(
TP
+
FP
)
⁢
(
TP
+
FN
)
⁢
(
TN
+
FP
)
⁢
(
TN
+
FN
)
(
3
)
wherein TP is a true-positive frequency, TN is a true-negative frequency, FP is a false-positive frequency, and FN is a false-negative frequency.

### Claim 5 (depends on 4)

The method of claim 4, wherein a modified MCC is calculated by Equation 4 by applying a condition of calculating the MCC by giving a weight of 5 to the TP so that an optimized condition attaches importance to the TP, and a condition of classifying TF (true false) data as the TP when the TP is over 10% of the TF data, and an optimization algorithm used for optimization when the modified MCC is the objective function is a Particle Swarm Optimization (PSO),
MCC
modified
=
5
×
TP
×
TN
-
FP
×
FN
(
5
×
TP
+
FP
)
⁢
(
5
×
TP
+
FN
)
⁢
(
TN
+
FP
)
⁢
(
TN
+
FN
)
(
4
)

### Claim 6 (depends on 1)

The method of claim 1, wherein as for the alert period, a range of 0.1 day to 14 days is designated as a search target at an early stage of attempting optimization, and is fixed as 1 day when final optimization is performed.

### Claim 7 (depends on 1)

The method of claim 1, wherein for the data of the maximum/minimum loads on the surface rod in the normal operation, average values for 2 weeks of a production period that is stably maintained are used, depending on target oil well fields, or theoretical maximum/minimum loads in the normal operation are used when there are target oil well, pump, and production liquid.

### Claim 8 (depends on 1)

The method of claim 1, wherein the scaled load ratio is calculated by Equation 1 and 2
Scaled
⁢
minimum
⁢
load
⁢
on
⁢
surface
⁢
rod
=
Current
⁢
minimum
⁢
load
on
⁢
surface
⁢
rod
Minimum
⁢
load
⁢
on
⁢
surface
rod
⁢
in
⁢
normal
⁢
operation
⁢
Scaled
⁢
minimum
⁢
load
⁢
on
⁢
surface
⁢
rod
=
Current
⁢
maximum
⁢
load
on
⁢
surface
⁢
rod
Maximum
⁢
load
⁢
on
⁢
surface
rod
⁢
in
⁢
normal
⁢
operation
(
1
)
Scaled
⁢
load
⁢
ratio
=
Scaled
⁢
minimum
⁢
load
⁢
on
⁢
surface
⁢
rod
Scaled
⁢
maximum
⁢
load
⁢
on
⁢
surface
⁢
rod
(
2
)

### Claim 9

A system for predicting failures of rod pumps using a scaled load ratio, the system comprising:
a storage device storing data in the system, the data comprising current maximum/minimum loads on a surface rod, a current pump speed obtained from a sensor installed at a rod pump, scaled load ratios, an average of the scaled load ratios in a rolling window, a ratio of abnormal events, a size of the rolling window, upper and lower bounds of a normal range of the scaled load ratio, an alert period, and an alert frequency ratio; and
a processor executing software using the data stored in the storage device, wherein the software predicts whether the rod pump has an abnormality by calculating the scaled load ratio on the basis of the current maximum/minimum loads on the surface rod stored in the storage device and data of maximum/minimum loads on the surface rod in normal operation.

### Claim 10 (depends on 9)

The system of claim 9, wherein the software includes an outlier removable module configured to remove outliers from the data received by the processor from the storage device on the basis of a set outlier removal reference.

### Claim 11 (depends on 10)

The system of claim 10, wherein the software includes a scaled load ratio calculation module configured to calculate the scaled load ratio using data that have undergone preprocesses such as outlier removal and scaling.

### Claim 12 (depends on 11)

The system of claim 11, wherein the software includes a scaled load ratio average calculation module configured to calculate the average the scaled load ratios in the rolling window by applying a rolling window method to the scaled load ratio to remove noises of the scaled load ratio.

### Claim 13 (depends on 12)

The system of claim 12, wherein the software includes a scaled load ratio-normal range determination and classification module configured to determine whether the average of the scaled load ratios is in the normal range, and classify the scaled load ratios as normal events and abnormal events.

### Claim 14 (depends on 13)

The system of claim 13, wherein the software includes a failure data ratio calculation and alert generation module configured to calculate a ratio of the abnormal events in the alert period, and to generate an alert when the ratio of the abnormal events exceeds the alert frequency ratio.

### Claim 15 (depends on 12)

The system of claim 12, wherein the software further includes an optimization module configured to optimize the size of the rolling window, the upper and lower bounds of the normal range of the scaled load ratio, the alert period, and the alert frequency ratio as optimal input values;
wherein the optimization is performed when the size of the rolling window, the upper and lower bounds of the normal range of the scaled load ratio, the alert period, and the alert frequency ratio are initially set as the optimal input values, or is performed when a rod pump is reinstalled, repaired, or replaced; and
wherein the size of the rolling window, the upper and lower bounds of the normal range of the scaled load ratio, the alert period, and the alert frequency ratio that are the optimal input values set in the optimization module are stored in the storage device.

### Claim 16 (depends on 15)

The system of claim 15, wherein a Matthews Correlation Coefficient (MCC) that is an index for evaluating analysis performance is used in an objective function that is used during optimization by the optimization module, and the MCC is calculated by Equation 3,
MCC
=
TP
×
TN
-
FP
×
FN
(
TP
+
FP
)
⁢
(
TP
+
FN
)
⁢
(
TN
+
FP
)
⁢
(
TN
+
FN
)
(
3
)
wherein TP is a true-positive frequency, TN is a true-negative frequency, FP is a false-positive frequency, and FN is a false-negative frequency.

### Claim 17 (depends on 16)

The system of claim 16, wherein a modified MCC is calculated by Equation 4 by applying a condition of calculating the MCC by giving a weight of 5 to the TP so that an optimized condition attaches importance to the TP, and a condition of classifying TF (true false) data as the TP when the TP is over 10% of the TF data, and an optimization algorithm used for optimization when the modified MCC is the objective function is a Particle Swarm Optimization (PSO),
MCC
modified
=
5
×
TP
×
TN
-
FP
×
FN
(
5
×
TP
+
FP
)
⁢
(
5
×
TP
+
FN
)
⁢
(
TN
+
FP
)
⁢
(
TN
+
FN
)
(
4
)

### Claim 18 (depends on 15)

The system of claim 15, wherein as for the alert period, a range of 0.1 day to 14 days is designated as a search target at an early stage of attempting optimization, and is fixed as 1 day when final optimization is performed.

### Claim 19 (depends on 9)

The system of claim 9, wherein the software includes a scaling module configured to receive data of maximum/minimum loads on the surface rod input and stored in the storage device by an operator via an interface, and to scale the data of the maximum/minimum loads on the surface rod into normal operation values to generate the data of the maximum/minimum loads on the surface rod in the normal operation.

### Claim 20 (depends on 19)

The system of claim 19, wherein for the data of the maximum/minimum loads on the surface rod in the normal operation, average values for 2 weeks of a production period that is stably maintained are used, depending on target oil well fields, or theoretical maximum/minimum loads in the normal operation are used when there are target oil well, pump, and production liquid.