Coupled Mudcake Model Predicts Near-Wellbore Permeability
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Solution Overview
Problem
Current methods for predicting changes in the near-wellbore area properties during drilling and cleaning operations are inadequate, as they fail to accurately account for the penetration and removal of drilling mud components, leading to reduced well productivity due to formation damage, and require numerous laboratory experiments for optimizing mud composition and drilling regimes.
Innovation Solution
A method combining mathematical modeling and laboratory filtration experiments, utilizing X-ray micro Computed Tomography to determine concentration curves of penetrated drilling mud particles, and developing coupled mathematical models for external and internal mudcakes to predict permeability and saturation changes in the near-wellbore area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional mathematical models are used to describe drilling mud invasion, then the modeling process is simplified, but the accuracy of predicting near-wellbore area properties deteriorates because these models assume drilling mud particles do not penetrate into reservoir rocks
Solution Approach 1:
The patent introduces new parameters to describe the concentration distribution of drilling mud particles within the near-wellbore area, moving beyond the binary assumption of particle penetration. By parameterizing the concentration field C(r,z,t) and its evolution, the model achieves higher prediction accuracy while maintaining mathematical tractability through partial differential equations that capture particle transport dynamics.
2Measurement precision
If detailed laboratory filtration experiments are conducted to account for penetrated drilling mud components, then the accuracy of permeability profiling improves, but the time and resource requirements increase significantly
Solution Approach 1:
The patent uses electrical resistance measurements as a proxy or copy of the actual permeability distribution. By measuring electrical resistance R(r,z,t) and using it to infer permeability k(r,z,t) through established relationships, the method obtains detailed permeability profiles without requiring physical core samples or lengthy filtration experiments, thus saving time while maintaining accuracy.
3Manufacturing precision
If numerical simulation with fine cylindrical grids is used to model invasion dynamics, then the spatial resolution of permeability distribution improves, but the computational complexity and data processing requirements increase
Solution Approach 1:
The patent extracts and measures the electrical resistance distribution directly from the near-wellbore area using multi-sonde induction logging, bypassing the need for complex numerical simulations with fine grids. This direct measurement approach obtains high-resolution spatial data without the computational burden of detailed numerical modeling, simplifying the overall process while maintaining precision.
4Adaptability or versatility
If multiple laboratory experiments are conducted to optimize drilling mud composition for complex multizone formations, then the suitability of mud composition for different zones improves, but the number of experiments and associated costs increase
Solution Approach 1:
The patent performs preliminary numerical simulation to predict the invasion dynamics and permeability changes for different drilling mud compositions and drilling regimes before conducting actual field operations. By using the developed mathematical model to screen and optimize mud compositions in silico, the method identifies suitable compositions for complex multizone formations without requiring numerous physical laboratory experiments, thus reducing time and resource consumption while maintaining adaptability.
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
This approach allows for precise prediction of near-wellbore area properties, reducing the need for extensive laboratory testing and enabling the optimization of drilling mud composition and cleaning regimes, thereby enhancing well productivity by accurately modeling mud invasion and removal dynamics.
Implementation Method 1
X-ray micro Computed Tomography to obtain concentration curves for penetrated drilling mud particles
Data Source
AI summary
In order to predict properties of a formation in a near-wellbore area exposed to a drilling mud rheological properties of the drilling mud, of a filtrate of the drilling mud and of a reservoir fluid are determined. Properties of an external mudcake, porosity and permeability of the core sample are determined. A mathematical model of the external mudcake is created. The drilling mud is injected through a core sample and dynamics of pressure drop across the sample and dynamics of a flow rate of a liquid leaving the sample are determined. Using an X-ray micro Computed Tomography a profile of concentration of particles of the drilling mud penetrated into the sample is determined. A mathematical model is developed for the internal mudcake to describe dynamics of changes in concentration of the particles of the drilling mud in a pore space of the core sample. A coupled mathematical model of the internal and the external mudcakes is created and parameters of the mathematical model of the internal mudcake are determined providing matching of simulation results to the experimental data on injection the drilling mud through the core sample and to the concentration profile of the particles of the drilling mud.