Abstract
Reservoir fluids frequently reveal complex phase behaviors in hydrocarbon columns owing to the effects of gravity, thermal diffusion, biodegradation, active charging, water washing, seals leaking, and so on. In addition, the formation compartmentalization often causing discontinuous distributions of fluid compositions and properties makes the proper fluid characterization and reservoir architecture even more challenging yet compelled. The recognition of compositional grading and flow barriers becomes a key to accurate formation evaluation in a cost effective manner. Downhole fluid analysis (DFA) of asphaltene gradients provides an excellent method to delineate the complexity of black oil columns. In this paper, a methodology was developed to estimate downhole asphaltene variations with depths using an equation-of-state (EOS) approach coupled with DFA measurements. DFA tools were used to determine fluid compositions of CO2, C1, C2, C3-C5, C6+, gas-oil ratio (GOR), density and the coloration (optical density) associated with asphaltene contents at downhole conditions. The delumping and characterization procedures proposed by Zuo et al. (2008) were employed to obtain the detailed compositions excluding asphaltenes. In addition, a molar mass distribution of asphaltenes was described by a three-parameter Gamma probability function. The Gaussian quadrature method was used to generate asphaltene pseudocomponents. Five pseudocomponents were employed to represent the normal asphaltene nanoaggregates. Asphaltene distributions in oil columns were computed by tuning the molar mass of asphaltene nanoaggregates against the DFA coloration logs at a reference depth. The methodology was successfully applied to investigate black oil reservoir connectivity (or flow barriers) for offshore field cases. The analysis results were consistent with the subsequent production data and analytical chemistry. Furthermore, for simplicity, it is reasonable to assume that asphaltenes have average properties such as molar mass in entire oil columns. The results obtained in this work demonstrate that the proposed method provides a useful tool to reduce the uncertainties related to reservoir compartmentalization and to optimize the DFA logging during acquisition.
Highlights
In the past few decades, fluid homogeneity has often been assumed in a reservoir
The results obtained in this work demonstrate that the proposed method provides a useful tool to reduce the uncertainties related to reservoir compartmentalization and to optimize the Downhole fluid analysis (DFA) logging during acquisition
This paper presented a methodology to analyze asphaltene grading with depth using the EOS approach and the DFA tools
Summary
Equilibrate the component of crude oil with by far the least mobility necessitates substantial permeability. As mentioned by Hoier and Whitson [4] and Mullins [5], for equilibrium fluid distributions, the variations of fluid compositions and properties are usually small with depth if the reservoir conditions are far away from the critical point and the saturation point (e.g. highly undersaturated black oil). The asphaltenes are dispersed in crude oils as nanoaggregates This information provides us a new powerful method of determining flow connectivity (barriers) in the reservoir by measuring asphaltene (coloration) contents with depth at downhole conditions, especially when bulk fluid property and compositional gradients are not observable. Asphaltenes in reservoir crude oils, dispersed as asphaltene nanoaggregates, have by far the lowest rate of diffusion compared to any crude oil components When they are in equilibrium throughout a column, massive fluid flow is indicated thereby positively constraining connectivity. The results show that the developed methodology can be integrated into the new workflow [14] as one useful means in analyzing asphaltene coloration gradients and in discerning reservoir connectivity
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