Abstract: Proposed is a pump failure prediction apparatus which includes at least one processor, a storage, which is communicably connected with the processor and stores a program code which operates in the processor, and a communicator, which is communicably connected with the processor, wherein the program code includes a data collection module, and an abnormality detection module which detects three abnormalities. The first abnormality appears before failure occurrence by inputting the real-time data into a first model which has performed supervised learning of history data. The second abnormality appears outside of a normal operation range of the pump by inputting the real-time data to a second, which has performed unsupervised learning of normal operation data. The third abnormality appears outside an initial normal operation range of the pump by inputting the real-time data to a third model, which has performed unsupervised learning of initial operation data.

Abstract: Proposed are a well log quality improvement apparatus and a well log quality improvement method. In an embodiment, a well log quality improvement method includes performing a quality controlling operation on a well log by inputting the well log to a well logging data processing model to train the model and by determining a bad hole section corresponding to a log section associated with a bad hole, performing a conditioning operation on the well log by replacing the bad hole section included in the well log with alternative data, and normalizing a distribution of data of the well log according to a distribution of data of a reference well log obtained from a reference well. By improving the quality of the well log, the overall accuracy of oil and gas exploration may be improved, and time required for data analysis may be reduced.

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.

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.