Proppant Flowback Mitigation via Simulator Model
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Solution Overview
Problem
Hydraulically fractured wells experience proppant flowback due to uneven proppant distribution and non-uniform loading, leading to proppant grains being dislodged and flowing back into the wellbore, causing production issues and potential loss of production.
Innovation Solution
A method involving a simulator model that calculates formation properties, flow pressures, and flow velocities to determine a normalized production rate, optimizing proppant flowback mitigation by adjusting production rates and using a z-factor vs. depth lookup table to manage fluid flow and pressure depletion across the wellbore.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If proppant is used in large quantities to stimulate hydraulic fractures, then fracture conductivity and production capacity are improved, but proppant flowback into the wellbore increases
Solution Approach 1:
The system performs preliminary calculations of formation properties, flow pressures, and flow velocities before production begins. A simulator model is used to predict proppant flowback risk and determine optimal production rates in advance, allowing operators to prevent flowback before it occurs rather than reacting after proppant has entered the wellbore.
Solution Approach 2:
The system continuously monitors actual production data and compares it with simulated predictions. The simulator model uses feedback from actual flow velocities and production rates to adjust and refine production rate recommendations, creating a closed-loop control system that adapts to changing downhole conditions and maintains optimal production while preventing proppant flowback.
2Productivity
If production rate is increased to maximize hydrocarbon recovery, then productivity improves, but fluid velocity increases causing proppant dislodgement and flowback
Solution Approach 1:
The system calculates critical velocity parameters and uses them to determine optimal production rates. By changing the production rate parameter to maintain fluid velocity below the critical threshold, the system maximizes hydrocarbon recovery while preventing proppant dislodgement. The simulator model dynamically adjusts production rate parameters based on calculated formation properties and flow conditions.
3Reliability
If fractures are allowed to close naturally after treatment, then proppant is trapped in place, but proppant settling and additional flowback occurs
Solution Approach 1:
The system performs preliminary calculations to determine the optimal timing for production initiation after fracturing treatment. By calculating formation properties and flow pressures in advance, the system identifies the window of opportunity to start production before fractures fully close, ensuring proppant remains suspended and trapped in place while preventing settling and additional flowback.
4Reliability
If frequent cleanup runs are performed to remove proppant from wellbore, then proppant-free production is maintained, but production time and operational complexity increase
Solution Approach 1:
The system enables the well to self-regulate production rates to prevent proppant flowback in the first place. By using the simulator model to calculate and maintain optimal production rates that keep fluid velocity below critical thresholds, the well maintains proppant-free production without requiring external intervention or frequent cleanup runs, thus avoiding production time loss and operational complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Effectively reduces proppant flowback by optimizing production rates and maintaining proppant in place, minimizing frequent cleanups and preventing production losses by stabilizing the proppant pack and controlling fluid velocities.
Implementation Method 1
using, by a simulator model, a material balance equation which considers the formation properties to determine pressure depletion for different zones of the wellbore
Implementation Method 2
generating, by the simulator model, a simulated flow velocity value based at least partly on the production rates, flow pressures, and pressure depletion
Implementation Method 3
generating a z-factor vs. depth lookup table for a plurality of fluid segments and time intervals
Data Source
AI summary
Proppant flowback during post-stimulation well clean up and production is a common occurrence in most hydraulically fractured wells. The production of the proppant from a propped fracture is related to the forces acting on the proppant pack during the well that is actively producing fluids. Flow rate and pressure data collected during the post-treatment flowback activity is used in simulating bottomhole (BH) production rates using a Gaussian solution scheme. The BH rate is distributed amongst the various perforation clusters while incorporating the effects of key hydraulic fracture characteristics in the presence of simulated effective bottomhole flowing pressures across different fluid entry points into the wellbore. The solution is updated at each time step during the simulation. The production allocation is then used in calculating effective flow velocities that are then compared with critical velocities to predict proppant flowback. Steps to mitigate or reduce the flowback are implemented.