Online measurment method for temperature stability of production layer in oil and gas well, system and storage medium

A system comprising a memory, a processor and computer programs stored in the memory and performed by the processor to implement an online measurement method;

• the method comprising the following steps:
• S10, obtaining a plurality of temperature data over time at each position point of an optical fiber;
• S20, according to the plurality of temperature data, calculating temperature standard deviations of each position point within a production layer of the oil and gas well at a plurality of time points within a preset time period;
• S30, performing probability distributions statistics according to the temperature standard deviations at all position points of the production layer at a time point, according to normal distribution;
• fitting a probability distribution curve of the temperature standard deviations at all position points of the production layer at the time point, and obtaining a probability density function according to the fitted curve;
• S40, according to the probability density function, calculating the temperature standard deviations corresponding to at least one value that integral values of the probability density function is between (0, 1);
• and
• S50, repeating the steps S30˜S40 to obtain the temperature standard deviations corresponding to the at least one value that the integral values of the probability density function of the temperature standard deviations at all position points of the production layer at each time point is between (0, 1), segmenting all the position points of the production layer, and generating a standard temperature deviation normal distribution probability time curve of each section of the production layer according to the temperature standard deviations.

A computer readable storage medium configured to store computer programs, the computer programs performed by a processor to implement an online measurement method, the method comprising the following steps:

• S10, obtaining a plurality of temperature data over time at each position point of an optical fiber;
• S20, according to the plurality of temperature data, calculating temperature standard deviations of each position point within a production layer of the oil and gas well at a plurality of time points within a preset time period;
• S30, performing probability distributions statistics according to the temperature standard deviations at all position points of the production layer at a time point, according to normal distribution;
• fitting a probability distribution curve of the temperature standard deviations at all position points of the production layer at the time point, and obtaining a probability density function according to the fitted curve;
• S40, according to the probability density function, calculating the temperature standard deviations corresponding to at least one value that integral values of the probability density function is between (0, 1);
• and
• S50, repeating the steps S30˜S40 to obtain the temperature standard deviations corresponding to the at least one value that the integral values of the probability density function of the temperature standard deviations at all position points of the production layer at each time point is between (0, 1), segmenting all the position points of the production layer, and generating a standard temperature deviation normal distribution probability time curve of each section of the production layer according to the temperature standard deviations.