Calibrating close interval survey data with remote monitoring data

A method for calibrating close interval survey (CIS) measurements, the method comprising:

• obtaining a plurality of CIS measurements from a plurality of CIS locations along a pipeline;
• obtaining a first plurality of remotely monitored measurements from a plurality of test stations positioned along the pipeline for a first time period;
• assigning, for each of the plurality of test stations, one of the plurality of CIS locations as an adjacent CIS location based on location data for the plurality of CIS locations and the plurality of test stations;
• calibrating the CIS measurements with the remotely monitored measurements by using the first plurality of remotely monitored measurements for each of the plurality of test stations as a proxy measurement for the adjacent CIS location;
• obtaining a second plurality of remotely monitored measurements from the plurality of test stations for the second time period;
• extrapolating the second plurality of remotely monitored measurements along the pipeline between two adjacent test stations of the plurality of test stations;
• and,
• projecting the plurality of CIS measurements to the second time period by adjusting the plurality of CIS measurements based on the extrapolation of the second plurality of remotely monitored measurements along the pipeline to obtain projected CIS potential measurements for the second time period.

A computer-implemented method for seasonally modelling close interval survey (CIS) potential measurements for a pipeline segment, the method comprising:

• validating CIS potential measurements taken along the pipeline segment during a first time period with remotely monitored potential measurements measured at a plurality of test stations along the pipeline segment during the first time period based on location data of the CIS potential measurements and the remotely monitored potential measurements;
• applying a seasonal variation model to the remotely monitored potential measurements to obtain seasonally adjusted potential measurements for the plurality of test stations for a second time period;
• applying an extrapolation of the seasonally adjusted potential measurements along the pipeline between two adjacent test stations of the plurality of test stations;
• and,
• projecting the CIS potential measurements to the second time period by adjusting the CIS potential measurements based on the extrapolation of the seasonally adjusted potential measurements along the pipeline to obtain projected CIS potential measurements for the second time period.

A computer-implemented method for seasonally modelling close interval survey (CIS) potential measurements, the method comprising:

• validating CIS potential measurements taken along a pipeline segment during a first time period with a first plurality of remotely monitored potential measurements measured at a plurality of test stations along the pipeline segment during the first time period;
• obtaining a second plurality of remotely monitored potential measurements measured at the plurality of test stations during a second time period;
• extrapolating the second plurality of remotely monitored potential measurements between two adjacent test stations of the plurality of test stations for the second time period;
• and,
• projecting the CIS potential measurements to the second time period by adjusting the CIS potential measurements from the first time period based on the extrapolation of the second plurality of remotely monitored potential measurements to obtain projected CIS potential measurements for the second time period.

A non-transitory computer readable medium containing computer instructions stored therein for causing a computer processor to perform the steps of:

• receiving close interval survey data from a close interval survey (CIS) performed at a plurality of CIS locations along a pipeline for a first time period;
• receiving remotely monitored data from a plurality of test stations positioned along the pipeline for the first time period;
• assigning, for each of the plurality of test stations, one of the plurality of CIS locations as an adjacent CIS location based on location data for the plurality of CIS locations and the plurality of test stations;
• calibrating the close interval survey data with the remotely monitored data by using the remotely monitored data for each test station of the plurality of test stations as a proxy measurement for the adjacent CIS location;
• applying a seasonal variation model to the remotely monitored data to obtain seasonally adjusted remotely monitored data for each test station of the plurality of test stations for a second time period;
• extrapolating the seasonally adjusted remotely monitored data along the pipeline between two adjacent test stations of the plurality of test stations to obtain seasonally adjusted remotely monitored data between the two adjacent test stations;
• and
• projecting the close interval survey data to the second time period by adjusting the close interval survey data based on the extrapolation of the seasonally adjusted remotely monitored data along the pipeline to obtain projected CIS potential measurements for the second time period.