Fractured Reservoir Simulation Dynamic Inversion

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Solution Overview

Problem

Current deterministic approaches to modeling fractured reservoirs are limited by approximations and lack of geological consistency, leading to suboptimal performance and resource-intensive manual modifications, which hinder efficient history matching and predictive accuracy in hydrocarbon exploration.

Innovation Solution

A closed-loop dynamic inversion method integrating high-resolution geological models, discrete fracture network models, and reservoir simulation models, enabling adaptive uncertainty quantification and multi-variate parameter control through a global optimization process, resulting in geologically consistent simulation models.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If deterministic data processing processes are used to model fracture corridors, then the modeling process is simpler and more straightforward, but the geological consistency of the fracture model deteriorates and manual modifications are required

Engineering Contradiction:
Improvemodeling process simplicityVSAvoidgeological consistency
Core Design Contradiction:
Ease of manufactureVSManufacturing precision

Solution Approach 1:

The patent implements a closed-loop dynamic inversion system where simulation results feed back into model parameter adjustments. The system continuously compares simulated production data with actual field data and automatically adjusts fracture network parameters (porosity, permeability, geometry) to minimize misfit, eliminating the need for manual box multiplier modifications while maintaining geological consistency throughout the history matching process

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The system enables self-adjusting fracture models through automated closed-loop inversion. The fracture network model automatically calibrates its own parameters by processing seismic data, borehole logs, and production data through the inversion algorithm, which dynamically adjusts fracture properties to match observed reservoir behavior without requiring external manual intervention

Inventive Principle:
Principle #25Self-service

2Reliability

If manual modifications and alterations are made to fracture models, then adjustments can be made to improve model performance, but the process becomes extremely resource-intense and time-consuming

Engineering Contradiction:
Improvemodel performanceVSAvoidhistory matching efficiency
Core Design Contradiction:
ReliabilityVSProductivity

Solution Approach 1:

The patent replaces the mechanical manual adjustment process with an automated computational inversion system. Instead of manually adjusting fracture parameters one at a time, the system uses numerical optimization algorithms to simultaneously adjust multiple fracture network parameters (porosity, permeability, block dimensions, orientation) based on objective function minimization, dramatically reducing the time and resources required for history matching

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system dynamically changes multiple fracture model parameters simultaneously through the closed-loop inversion process. Rather than sequential manual adjustments, the inversion algorithm computes optimal values for fracture porosity, permeability, block length, and orientation parameters together, achieving model calibration much faster while improving overall model performance

Inventive Principle:
Principle #35Parameter changes

3Device complexity

If fractures are extended from top to bottom of the simulation grid to reduce spatial complexity, then the model becomes simpler, but the geological realism and representativeness of fracture properties deteriorate

Engineering Contradiction:
Improvespatial complexityVSAvoidfracture property representativeness
Core Design Contradiction:
Device complexityVSManufacturing precision

Solution Approach 1:

The patent applies local quality by allowing fracture properties to vary spatially throughout the reservoir model. The discrete fracture network assigns different porosity, permeability, and geometric parameters to individual fracture blocks based on local geological conditions, seismic attributes, and borehole data, rather than applying uniform properties across the entire grid, thereby maintaining both model manageability and geological realism

Inventive Principle:
Principle #3Local quality

4Ease of manufacture

If fracture properties are assigned simplistically without representative spatial variations, then the modeling process is easier, but the geological consistency and predictive accuracy deteriorate

Engineering Contradiction:
Improveparameter assignment simplicityVSAvoidpredictive accuracy
Core Design Contradiction:
Ease of manufactureVSMeasurement precision

Solution Approach 1:

The system performs preliminary action by pre-processing seismic and borehole data to generate spatial distribution maps of fracture properties before running the simulation. The inversion system uses pre-computed fracture indicators from seismic attributes and borehole image logs to initialize and constrain the fracture network parameters, enabling realistic spatial variation without requiring complex manual parameter assignment during the modeling process

Inventive Principle:
Principle #10Preliminary action

Data Source

PatentEP3938815B1Method for dynamic calibration and simultaneous closed-loop inversion of simulation models of fractured reservoirs
Publication Date: 2023.01.25 SAUDI ARABIAN OIL CO
  • EP3938815B1 patent drawingFigure 1
  • EP3938815B1 patent drawingFigure 2
  • EP3938815B1 patent drawingFigure 3

AI summary

Systems and methods for generating a fractured reservoir model include: receiving a seismic dataset of a surveyed subsurface; identifying a dynamic response of each parameter; selecting a subset of parameters from the set of parameters based on the dynamic response of each parameter; sampling an outer boundary of a parameter uncertainty domain; adjusting the range of values associated with each parameter of the subset based on the sampling; generating a geo-model based on the adjusted range of values associated with each parameter of the subset; generating a discrete fracture network model based on the geo-model; generating a scenario of a simulation model based on the discrete fracture network model and the geo-model; performing a forward simulation based on the scenario of the simulation model; determining that a misfit of the forward simulation is below a threshold by evaluating an objective function; and producing a model based on the forward simulation.