Methods and systems for predicting risk of early-screen-out in near-well zone based on distributed fiber acoustic sensing (das)

A method for predicting a risk of early screen-out in a near-well zone based on distributed fiber acoustic sensing (DAS), comprising following operations:

• S10, laying distributed optical fibers in a horizontal well to be fractured by a continuous tubing technology, and installing the distributed optical fibers on an outer side of a production casing or an outer side of a packer tubing column;
• S20, collecting geological and engineering parameters of a reservoir of the horizontal well to be fractured, and establishing any reasonable numerical model for calculating a fracture extension of a fluid-solid coupled and high-velocity horizontal well fracture slit;
• S30, performing construction operation of multi-stage hydraulic fracturing of the shale gas well S2 in multiple clusters, and transmitting acoustic signals during the fracturing process through the optical fibers, and processing the acoustic signals as variations in energy values with time;
• and collecting construction pressure monitoring data:
• S40, calibrating a distribution range of acoustic signal energy values corresponding to locations of perforation clusters of the horizontal well based on depths of the perforation clusters and change data of the acoustic signal energy values determined in a construction design;
• S50, obtaining sound energy of each perforation cluster within a time period by calculating a sum of all the energy values within the distribution range of the acoustic signal energy values of the locations of the perforation clusters within each time period;
• S60, obtaining corrected sound energy by processing data curves of variations of the sound energy of each perforation cluster within a historical time period using a specific weighted moving average filter;
• S70, calculating a fracturing fluid flow velocity of each perforation cluster within the time period based on the corrected sound energy;
• S80, calculating a perforation friction resistance pressure drop of each perforation cluster using an existing reasonable friction resistance formula based on the calculated fracturing fluid flow velocity of each perforation cluster and perforation parameters of each perforation cluster:
• S90, substituting the fracturing fluid flow velocity of each perforation cluster calculated in the S70 into the numerical model for calculating the fracture extension of the horizontal well fracturing slit to simulate and predict further extension behaviors and morphological changes of the hydraulic fracture slit and output a predicted fracture slit morphological result and the slit fluid pressure of the hydraulic fracture of each perforation cluster;
• determining an actual fluid pressure of each perforation cluster at a bottom of the well based on the monitoring construction pressure data and wellbore friction resistance;
• and calculating a near-well friction resistance pressure drop of the hydraulic fracture slit of each perforation cluster;
• p
• n
• ,
• i
• =
• p
• r
• ,
• i
• -
• p
• p
• ,
• i
• -
• p
• f
• ,
• i
• where pn,i denotes a near-well friction resistance pressure drop of an ith fracture slit in MPa;
• pr,i denotes an actual fluid pressure at the location of the ith perforation cluster in MPa;
• and pf,i denotes a slit fluid pressure of the ith fracture slit in MPa:
• S100, calculating a near-well friction resistance coefficient of the fracture of each perforation cluster based on the near-well friction resistance pressure drop of the hydraulic fracture slit of each perforation cluster;
• and
• S110, determining the risk of early screen-out in the near-well zone based on a change rule of the near-well friction resistance coefficient over time.