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Asphaltene Deposition and Fouling in Reservoirs

Authors: Mohammad Tavakkoli; Peng He; Pei-Hsuan Lin; Sara Rezaee; Maura Puerto; Rocio Doherty; Jefferson Creek; +6 Authors

Asphaltene Deposition and Fouling in Reservoirs

Abstract

In this paper, we will highlight some of the impactful collaborative efforts completed within DeepStar Phase XII of the X200 Flow Assurance committees leading to the development, integration and deployment of novel technologies. This project aims to establish in what cases asphaltene deposition in reservoirs is a real problem. Flow reduction can occur in deepwater wells, which manifests as effective "skin" or high pressure drawdown required for fluid flow to be maintained. It is typically concluded, without additional evidence, that such problems are the result of asphaltene deposition. Some models for asphaltene deposition were developed between 1990 and 2005. However, the principal obstruction to validation of these models has been a credible core flow test to show increased flow restriction with depositing asphaltenes. At present, operators are unable to estimate the risk of development due to asphaltene deposition in reservoirs and the perceived flow impairment. To best assess the treatment frequency and effectiveness that is required for project development and execution, there is a need to be able to correctly predict the rate of formation damage in reservoirs from asphaltene deposition and develop effective remediation treatments. A successful project will provide test protocol, results, and analysis tools that can be applied to risk management evaluation for asphaltene fouling in reservoirs. Asphaltene precipitation and deposition in the production tubing and surface facilities is a well- documented issue and different methods are available to manage this problem. However, the problems that asphaltenes may cause in the reservoir, especially in the near-wellbore region, are much less understood. There is a lack of experimental capability to properly identify this problem and evaluate the corresponding potential strategies for prevention and/or remediation if/when needed. In addition, the available modeling tools to account for this problem have limited capabilities. Within this project, we aim to develop experimental procedures and modeling methods to establish whether impairment caused by asphaltene deposition in reservoirs is a real problem or not, and to develop an understanding of the mechanisms by which asphaltene precipitate, alter wettability and potentially deposit in the formation obstructing flow. A new experimental setup for Saturates, Aromatics, Resins, and Asphaltenes (SARA) characterization was designed and implemented in the lab to perform faster and more reliable analyses. Core flood experiments have been designed and successfully executed to induce the precipitation of asphaltenes inside the core upon addition of an asphaltene precipitant (e.g., n-pentane or n-heptane), which is crucial to obtain more meaningful and more representative experimental conditions. It has been observed that when n-pentane is used to precipitate asphaltenes, even though asphaltene aggregates are present in the system, the core flood test results do not show apparent damage to permeability. However, when asphaltenes are precipitated upon addition of n-heptane, aggregates have a more solid-like structure, which in turn have more tendency to block the pore throats. A microfluidic device was developed and used to visualize asphaltene deposition in porous media, at ambient pressure and different temperatures, flow rates, and driving force of asphaltene precipitation. The test results obtained from microfluidic device are in good agreement with the test results from the core flood experiments. A Computational Fluid Dynamic model based on Lattice-Boltzmann theory was developed to simulate asphaltene deposition inside porous media and is being validated for the capability to scale up lab results to field conditions.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Average
Average
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