CO2 Flooding Well Pattern Selection Under Incomplete Miscibility
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Solution Overview
Problem
Existing well pattern selection methods for CO2 injection in low permeability reservoirs do not consider incomplete miscible displacement characteristics, leading to errors in recovery rate evaluation, gas breakthrough time prediction, and oil-gas migration laws, making it challenging to formulate effective development plans.
Innovation Solution
A well pattern optimization method that integrates reservoir recovery rate, cumulative oil production, oil exchange ratio, and social factors, using fluid component data and three-dimensional reservoir modeling to simulate different CO2 flooding well patterns, analyzing fronts and production parameters to determine the optimal pattern.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional well pattern selection methods are used without considering incomplete miscible displacement characteristics, then well pattern planning can be completed with simpler methods, but recovery rate evaluation contains errors and gas breakthrough time prediction is inaccurate
Solution Approach 1:
The patent applies parameter changes by introducing the minimum miscible pressure parameter and incomplete miscible displacement characteristics into the well pattern selection process. By establishing a three-dimensional reservoir model that incorporates pressure distribution, CO2 solubility, and displacement efficiency parameters, the method transforms the traditional single-parameter well pattern selection into a multi-parameter optimization system that accurately evaluates recovery rates and predicts gas breakthrough times under incomplete miscible conditions.
Solution Approach 2:
The patent transitions from conventional two-dimensional well pattern analysis to three-dimensional reservoir modeling that includes vertical pressure gradients, horizontal displacement fronts, and temporal evolution of miscible boundaries. This dimensional expansion enables accurate prediction of gas breakthrough timing and recovery rate evaluation by capturing the complex spatial-temporal characteristics of incomplete miscible displacement in low permeability reservoirs.
2Productivity
If CO2 injection is used in low permeability reservoirs, then crude oil viscosity reduction and extraction capability improve, but pressure funnel phenomenon occurs between injection and production wells
Solution Approach 1:
The patent applies preliminary action by establishing a three-dimensional reservoir model before CO2 injection to predict pressure distribution patterns and identify potential pressure funnel formation. The model pre-calculates optimal well pattern configurations that prevent severe pressure gradients, allowing operators to select well patterns that maintain uniform pressure distribution while achieving effective crude oil extraction in low permeability reservoirs.
Solution Approach 2:
The patent introduces the three-dimensional reservoir model as an intermediary tool that mediates between CO2 injection requirements and pressure distribution constraints. The model acts as a virtual test bed to evaluate how different well patterns affect pressure funnels, enabling selection of configurations that balance extraction capability with pressure uniformity without requiring actual injection trials.
3Stress or pressure
If five-spot well pattern is used, then reservoir pressure maintenance and flow capacity are improved, but control effect on individual wells is limited
Solution Approach 1:
The patent applies dynamics by transforming the static well pattern selection into a dynamic optimization process. The three-dimensional reservoir model enables real-time evaluation of how different well patterns perform under varying pressure conditions and production stages. Operators can dynamically adjust well pattern selection based on simulated pressure distribution and recovery rate predictions, achieving both pressure maintenance and individual well control flexibility.
4Area of stationary object
If inverted seven-spot well pattern is used, then sand body control and injection-production intensity are improved, but adjustment to well patterns in later stage is difficult
Solution Approach 1:
The patent applies preliminary action by using the three-dimensional reservoir model to pre-evaluate the long-term adaptability of different well patterns. The model predicts how inverted seven-spot and other patterns perform under various production scenarios, allowing operators to select configurations that maintain both sand body control and future adjustment flexibility before actual field development begins.
5Productivity
If inverted nine-spot well pattern is used, then oil production speed in early stage is improved, but injection-production well spacing is uneven leading to early gas breakthrough
Solution Approach 1:
The patent applies dimensional analysis by using three-dimensional reservoir modeling to evaluate well spacing distribution in inverted nine-spot patterns. The model identifies uneven spacing configurations that lead to early gas breakthrough by visualizing displacement fronts in three dimensions, enabling optimization of well locations to maintain high early production while preventing premature gas arrival at production wells.
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
Improves recovery rate evaluation and gas breakthrough time prediction by clarifying displacement characteristics, providing a rational design for CO2 injection development plans that enhance economic and social benefits.
Implementation Method 1
The displacement in this case is called incomplete miscible displacement
Implementation Method 2
due to the relatively small pores, narrow throats, and poor connectivity between pores
Data Source
AI summary
A well pattern optimization method based on CO2 incomplete miscible displacement characteristics is provided, including: obtaining fluid component data of formation crude oil, and establishing a fluid component model based on the fluid component data; establishing a three-dimensional reservoir model based on the fluid component model, and setting reservoir parameters for the three-dimensional reservoir model; performing simulation operation on the three-dimensional reservoir model with set reservoir parameters under different CO2 flooding well pattern modes, and obtaining simulation operation results; and performing analysis of fronts and production parameter comparison on the simulation operation results, and obtaining an optimal CO2 flooding well pattern mode.