Systems and methods for detecting fracture-driven interactions and identifying fracture-driven interaction risk in a subsurface volume of interest

A non-transitory computer-readable storage medium having instructions embodied thereon, the instructions being executable by a physical computer processor to perform a method for detecting fracture-driven interactions in a subsurface volume of interest, the method comprising:

• obtaining wellbore production data corresponding to the subsurface volume of interest from non-transitory storage medium;
• generating, with a physical computer processor, a trend of the wellbore production data by applying a filter to the wellbore production data;
• generating, with the physical computer processor, threshold parameters based on the wellbore production data, wherein the threshold parameters are used to set boundaries on the wellbore production data;
• generating, with the physical computer processor, fracture-driven interaction candidate data for a parent well by applying the trend and the threshold parameters to the subsurface data, wherein the fracture-driven interaction candidate data is a subset of the wellbore production data that exceed the ranges generated by the threshold parameters;
• identifying, with the physical computer processor, an active child well in a threshold spatial region around the parent well corresponding to a coincident time of the fracture-driven interaction candidate data for the parent well;
• identifying, with the physical computer processor, potentially interactive wellbore production data corresponding to the active child well during the coincident time;
• and
• detecting, with the physical computer processor, the fracture-driven interaction event based on the potentially interactive wellbore production data and the fracture-driven interaction candidate data.

A method for identifying fracture-driven interaction risk in a subsurface volume of interest, the method being implemented in a computer system that comprises a physical computer processor and non-transitory storage medium, the method comprising:

• obtaining an initial fracture-driven interaction model from a non-transitory storage medium, wherein the initial fracture-driven interaction model comprises fracture-driven interaction parameters that affect the fracture-driven interactions in the subsurface volume of interest;
• obtaining, from the non-transitory storage medium, training fracture-driven interaction event data;
• obtaining, from the non-transitory storage medium, training fracture-driven interaction event probability data;
• training, with the physical computer processor, the initial fracture-driven interaction model to generate a conditioned fracture-driven interaction model predicting fracture-driven interaction risk based on the training fracture-driven interaction event data and the fracture-driven interaction event probability data, wherein the conditioned fracture-driven interaction model comprises a subset of the fracture-driven interaction parameters that have a greater effect on the fracture-driven interactions in the subsurface volume of interest;
• and
• storing the conditioned fracture-driven interaction model.

A system for identifying fracture-driven interaction risk in a subsurface volume of interest, the system comprising:

• non-transitory storage medium;
• a physical computer processor configured by machine readable instructions to:
• obtain target fracture-driven interaction event data corresponding to the subsurface volume of interest from the non-transitory storage medium;
• obtain a conditioned fracture-driven interaction model from the non-transitory storage medium, the conditioned fracture-driven interaction model having been trained by applying training data to an initial fracture-driven interaction model, wherein the conditioned fracture-driven interaction model comprises fracture-driven interaction parameters that affect the fracture-driven interactions in the subsurface volume of interest, and wherein the training data includes (i) training fracture-driven interaction event data for the subsurface volume of interest and (ii) training fracture-driven interaction event probability data;
• and
• generate, with the physical computer processor, target fracture-driven interaction event probability data by applying the conditioned fracture-driven interaction model to the target wellbore production data.