Sensing-Based Unstable Asphaltene Estimation Under Pressurized Oil Conditions
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Solution Overview
Problem
Current laboratory methods for determining asphaltene content in oil samples are not representative of real-world conditions, as they are performed at atmospheric pressure and do not account for the continuous changes in volume fraction of alkanes under pressurized conditions, leading to inaccurate predictions of asphaltene deposition and frequency of cleaning jobs in oil extraction operations.
Innovation Solution
A method using a sensing device, such as a quartz crystal resonator, to measure the deposition rate of primary unstable asphaltenes under varying parameters like temperature, pressure, and alkane addition, calculating their concentration based on a diffusion coefficient and hydrodynamic radius, allowing for a continuous and single experiment to estimate asphaltene content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If centrifugation method is used to measure asphaltene concentration at atmospheric pressure, then measurement precision is improved, but the results are not representative of real-world pressurized conditions
Solution Approach 1:
The patent changes the pressure parameter from atmospheric pressure to pressurized conditions (up to 100 bar) to match real-world oil extraction conditions. This allows the measurement system to accurately reflect asphaltene behavior under actual operational parameters, resolving the contradiction between measurement precision and result representativeness.
Solution Approach 2:
The patent introduces a pressurized cell with controlled pressure and temperature conditions as an intermediary system between the laboratory measurement and real-world conditions. This intermediary environment enables accurate measurement while maintaining representativeness of real-world pressurized conditions.
2Measurement precision
If physical separation methods are used to determine asphaltene content, then measurement precision is improved, but the process requires large quantities of samples and is complicated to implement
Solution Approach 1:
The patent replaces complex mechanical separation systems (centrifuges, filters) with a sensing device that directly measures asphaltene deposition under pressurized conditions. This substitution eliminates the need for large sample quantities and complex separation infrastructure while maintaining measurement precision.
Solution Approach 2:
The patent extracts the essential measurement function from the complex separation process. Instead of requiring complete physical separation of asphaltenes, the method directly measures their deposition rate onto a sensing device, simplifying the overall process while maintaining precision.
3Reliability
If laboratory tests are performed under pressurized conditions, then reliability of results is improved, but the complexity of implementing separation methods increases
Solution Approach 1:
The patent replaces complex mechanical separation methods with a direct sensing measurement system under pressurized conditions. The sensing device measures asphaltene deposition directly without requiring centrifugation or filtration, thereby maintaining reliability while reducing implementation complexity.
Solution Approach 2:
The sensing device performs both the measurement and the separation function simultaneously. By monitoring the deposition of asphaltenes directly onto the sensor surface under pressurized conditions, the system eliminates the need for separate complex separation procedures.
4Productivity
If continuous monitoring under varying parameters is implemented, then productivity is improved, but the device complexity increases
Solution Approach 1:
The sensing device serves multiple functions: it measures asphaltene deposition rate, monitors the effects of pressure and temperature variations, and provides data for predicting cleaning frequency. This multi-functionality enables improved productivity without proportionally increasing device complexity.
Solution Approach 2:
The system continuously monitors asphaltene deposition under varying pressure and temperature conditions, providing real-time feedback that enables dynamic adjustment of operational parameters and optimization of cleaning schedules, thereby improving productivity.
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
Enables accurate estimation of unstable asphaltene concentration and deposition rate, optimizing the frequency of cleaning jobs and improving oil recovery by providing a solubility curve applicable to real-world conditions.
Implementation Method 1
measuring a deposition rate of asphaltenes deposited on the sensing device
Implementation Method 2
A method using a sensing device, such as a quartz crystal resonator, to measure the deposition rate
Implementation Method 3
calculating a concentration of unstable asphaltenes from the measured deposition rate of asphaltenes and a diffusion coefficient of primary unstable asphaltenes
Implementation Method 4
varying at a least one parameter among temperature of the oil sample, pressure and amount of alkanes added to the oil sample
Implementation Method 5
the volume fraction of light constituents present in the oil increases and the density of the carrier liquid decreases at pressures larger than the saturation point
Implementation Method 6
these asphaltenes tend to settle or to accumulate on the inner walls of the pipes
Data Source
Figure 1~3
Figure 4~5
Figure 6~7
AI summary
The present document concerns a method for estimating an unstable asphaltene content in an oil sample, the method comprising: a) placing a sensing device in a cell; b) causing the oil sample to flow in the cell; c) varying at a least one parameter among temperature of the oil sample, pressure and an amount of alkanes added to the oil sample; d) measuring a deposition rate of asphaltenes deposited on the sensing device as the at a least one parameter varies; and e) calculating a concentration of unstable asphaltenes from the measured deposition rate of asphaltenes and a diffusion coefficient of primary unstable asphaltenes present in the oil sample estimated based on a hydrodynamic radius of the primary unstable asphaltenes.