Big data technology-based oil well parameter intelligent early warning system and early warning method

Abstract

The invention discloses a big data technology-based oil well parameter intelligent early warning system and a big data technology-based oil well parameter intelligent early warning method. The early warning system comprises a display layer, an application layer, a model layer and a data layer; the data layer is used for collecting and integrating the historical data of various parameters in each oil well and providing the historical data to the model layer; the model layer stores the data and pre-processes the data; a prediction model is established through the training and learning of an alarm classifier, so that the prediction model can be adopted to perform early warning according to the work of the oil wells; the application layer calculates a curve threshold value by utilizing the model layer so as to determine a single-well abnormal alarm and perform inter-well correlation analysis; and analysis results and early-warning results are displayed to a user through the display layer.The early warning method comprises the following steps of: step 1, historical data acquisition; step 2, data preprocessing; and step 3, the training and learning of an alarm classifier.

Description

technical field [0001] The invention relates to intelligent early warning. In particular, an intelligent early warning system and early warning method for oil well parameters based on big data technology. Background technique [0002] With the continuous advancement of the construction of "smart oilfields", the amount of data integrated by the oil well production monitoring platform is increasing day by day. Major oilfields are studying the use of production big data for data mining, improving the alarm and early warning function modules, so as to realize automatic early warning and advanced early warning. The intelligent water that promotes production control, production analysis and production decision-making continues to improve. [0003] By analyzing complex and diverse data, big data technology can establish a model with the ability to "adapt" and "learn" to data changes, so that the calculation results of the model can be dynamically adjusted as the data changes. Big...

AI Technical Summary

Problems solved by technology

When the unified threshold is actually used, frequent false alarms are very likely to occur, causing the operator to "alarm numb", it is difficult to dynamically reflect changes in the environment (seasons, temperature, etc.), and it is impossible to independently distinguish the overrun caused by the above-mentioned measures and well shutdown maintenance, and cannot reflect different areas. The working conditions of different blocks and different well positions are different, and the workload of manual intervention is huge, which may easily cause partial early warning failure

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