Processes for monitoring corrosion and carrying out operational plans using same

1 . A process, comprising:

acquiring a plurality of corrosion factors for at least one well;

acquiring a plurality of corrosion loss logs for the at least one well, wherein the plurality of corrosion loss logs includes time lapse corrosion metal loss data;

providing the plurality of corrosion factors and the plurality of corrosion loss logs to a repository;

generating prepared data by cleaning, manipulating, converting, adjusting, biasing, or providing time normalization to the plurality of corrosion factors and the plurality of corrosion loss logs of the repository;

providing the prepared data to a machine learning model, wherein the machine learning model comprises a retraining model that in operation updates the machine learning model using one or more changes to the repository and/or using direct data input to the machine learning model, wherein updating the machine learning model via the retraining model further comprises utilizing new data comprising the one or more changes to the repository and/or the direct data input to the machine learning model in combination with data drift observed in the machine learning model to self-correct the machine learning model;

generating a corrosion prediction via the machine learning model utilizing the prepared data;

combining at least the plurality of corrosion factors, the plurality of corrosion loss logs, and the corrosion prediction into a user dashboard, wherein the user dashboard comprises:

a user interface that includes filters based on a type of casing, a type of field, a type of formation, a type of well, an intervention, or a well history to allow for a focused analysis;

insights into a sensitivity of corrosion rate to different environmental variables;

corrosion heatmaps comprising an indication corresponding to a spread of corrosion or a severity of corrosion overview across one or more locations in a field corresponding to the at least one well or a reservoir corresponding to the at least one well;

corrosion hotspots comprising a second indication of a depth of the at least one well where the corrosion is the highest in the at least one well;

primary causative factors; and

a risk profile;

using the user dashboard to determine an operational plan for the at least one well; and

carrying out the operational plan for the at least one well.

2 . The process of claim 1 , wherein the plurality of corrosion factors comprise two or more of: an age of the well, a location of the well, a lithology of the well, injection rates into the well, production rates recovered from the well, a salinity within the well, a pressure within the well, a temperature within the well, a completion quality of the well, a presence of a nearby aquifer, a presence of cement behind a casing in the well, a fluid type in a borehole of the well, a presence of an external coating, a H 2 S concentration in the well, and a CO 2 concentration in the well.

3 . The process of claim 1 , wherein the plurality of corrosion loss logs comprises logging data acquired from one or more mechanical tools, one or more ultrasonic tools, one or more electromagnetic tools, or a combination thereof.

4 . The process of claim 1 , wherein the repository is updated using a new plurality of corrosion factors and/or a new plurality of corrosion loss logs from the at least one well or from at least one additional well.

5 . The process of claim 1 , wherein the corrosion prediction comprises a present percentage of metal loss by mass, a dynamic corrosion rate, a future percentage of metal loss by mass, an estimated service lifetime of the at least one well, or a combination thereof.

6 . The process of claim 1 , further comprising utilizing the different environmental variables to identify primary causative factors to plan a well workover, plan a remedial action at the well, or plan other mitigation measures as the operational plan for the at least one well.

7 . The process of claim 1 , wherein the operational plan comprises at least one of planning a well workover, planning a well remediation, planning a corrosion mitigation operation, planning a well completion, and planning a well operation schedule.

8 . The process of claim 1 , wherein the machine learning model comprises user defined and controlled input weights.

9 . The process of claim 1 , wherein the machine learning model provides a ranking of the corrosion factors according to a corrosion contribution value.

10 . The process of claim 1 , further comprising:

using the user dashboard to determine a second operational plan for at least one new well; and

completing the at least one new well using the second operational plan.

11 . A process for predicting corrosion to complete a new well, the process comprising:

acquiring a plurality of corrosion factors for at least one well;

acquiring a plurality of corrosion loss logs for the at least one well, wherein the plurality of corrosion loss logs includes time lapse corrosion metal loss data;

providing the plurality of corrosion factors and the plurality of corrosion loss logs to a repository;

generating prepared data by cleaning, manipulating, converting, adjusting, biasing, or providing time normalization to the plurality of corrosion factors and the plurality of corrosion loss logs of the repository;

providing the prepared data to a machine learning model;

generating a corrosion prediction via the machine learning model utilizing the prepared data;

combining at least the plurality of corrosion factors, the plurality of corrosion loss logs, and the corrosion prediction into a user dashboard, wherein the user dashboard comprises:

a user interface that includes filters based on a type of casing, a type of field, a type of formation, a type of well, an intervention, or a well history to allow for a focused analysis;

insights into a sensitivity of corrosion rate to different environmental variables;

corrosion heatmaps comprising an indication corresponding to a spread of corrosion or a severity of corrosion overview across one or more locations in a field corresponding to the at least one well or a reservoir corresponding to the at least one well;

corrosion hotspots comprising a second indication of a depth of the at least one well where the corrosion is the highest in the at least one well;

primary causative factors; and

a risk profile;

using the user dashboard to determine an operational plan for at least one new well; and

completing the at least one new well using the operational plan.

12 . The process of claim 11 , wherein the plurality of corrosion factors comprise two or more of: an age of the well, a location of the well, a lithology of the well, injection rates into the well, production rates recovered from the well, a salinity within the well, a pressure within the well, a temperature within the well, a completion quality of the well, a presence of a nearby aquifer, a presence of cement behind a casing in the well, a fluid type in a borehole of the well, a presence of an external coating, a H 2 S concentration in the well, and a CO 2 concentration in the well.

13 . The process of claim 11 , wherein the corrosion prediction comprises a present percentage of metal loss by mass, a dynamic corrosion rate, a future percentage of metal loss by mass, an estimated service lifetime of the at least one well, or a combination thereof.

14 . The process of claim 11 , wherein the machine learning model comprises a retraining model that in operation updates the machine learning model using one or more changes to the repository.

15 . The process of claim 11 , wherein the machine learning model includes user defined and controlled input weights.

16 . The process of claim 11 , wherein the machine learning model provides a ranking of the corrosion factors according to a corrosion contribution value.

17 . The process of claim 11 , further comprising utilizing the different environmental variables to identify primary causative factors to plan at least one of a workover, a remedial action, or other mitigation measures as the operational plan for the at least one new well.