Oil production data frequent pattern mining method based on weak wildcard

A frequent pattern and production data technology, applied in data mining, electronic digital data processing, other database retrieval, etc., can solve problems such as inability to predict fluid production, achieve rich meaning, low time complexity, and overcome noise interference Effect

Inactive Publication Date: 2016-11-09
SOUTHWEST PETROLEUM UNIV
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Problems solved by technology

[0040] Aiming at the deficiencies of the prior art, the present invention provides a method for mining frequent patterns of petroleum production data based on weak wildcards, so as to solve the problem that the prior art cannot accurately predict the liquid production volume

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  • Oil production data frequent pattern mining method based on weak wildcard
  • Oil production data frequent pattern mining method based on weak wildcard
  • Oil production data frequent pattern mining method based on weak wildcard

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Embodiment Construction

[0060] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below with reference to the accompanying drawings and examples.

[0061] Because of the nature of oil daily fluid production data, direct predictions of production are unreliable. The present invention intends to change the way of thinking, convert the time-series data of daily fluid production in the oilfield into a coding sequence, and then perform frequent pattern mining to obtain the frequent pattern of the production sequence of the oil well, which is used to describe the fluid production of the oil well.

[0062] Example:

[0063] Step 1: Convert the time series data of oilfield daily fluid production into coded sequences

[0064] The 365-day liquid production of an oil well is converted into a coding sequence by coding. According to the characteristics of the data, it is found that the fluctuation of the produ...

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Abstract

The invention discloses an oil production data frequent pattern mining method based on weak wildcard, and relates to the field of data mining. The oil production data frequent pattern mining method based on the weak wildcard comprises the steps that 1, oil field daily fluid production time series data is converted into a coding sequence; 2, the coding sequence is mined to obtain different types of frequent sequence patterns, and an oil well is comprehensively depicted from various angles. The method has the advantages that the mining problem of three frequent sequence patterns is defined, the different types of frequent patterns can be mined from actual oil well production data, and the oil well is comprehensively depicted from the different angles; an algorithm is simple and efficient, a pruning algorithm is achieved, the time complexity is low, and the method is conveniently achieved in real time; a pattern filter technique is proposed, the different types of frequent patterns such as the powerful pattern, the special pattern and the popular pattern can be obtained through filtration for the different requirements; the method can be widely applied to various time series data.

Description

technical field [0001] The invention relates to the field of data mining, in particular to a method for mining frequent patterns of oil production data based on weak wildcards. Background technique [0002] A time series is a collection of observations arranged in time order. In the fields of engineering, economics, natural and social sciences, etc., there are a large number of such observation data. The order and size of this type of data reflect the information contained in the data and the interrelationships within the data. It is this interconnection or correlation that characterizes the "dynamics" or "memory" of the phenomena, processes, systems that produced these data. Once this correlation is described quantitatively, its future value can be predicted from the past value of the system. [0003] Time series analysis is a method of analyzing various interdependent and ordered discrete data sets. Its research object is a string of dynamic data that changes over time...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/90G06F2216/03
Inventor 汪敏闵帆邓魁苏赋李志伟
Owner SOUTHWEST PETROLEUM UNIV
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