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Abstract 3D pore-scale imaging and analysis provides an understanding of microscopic displacement processes and potentially a new set of predictive modeling tools for estimating multiphase flow properties of core material. Reconciliation and integration of the data derived from these models requires accurate characterization of the pore-scale distribution of fluids and a more detailed understanding of the role of wettability in oil recovery. The current study reports experimental imaging progress in these endeavors for a preserved-state carbonate core from a Middle Eastern waterflooded reservoir. Micro-CT methods were used in combination with novel fluid X-ray contrasting techniques and image registration to visualize the 3D pore-scale distribution of residual oil in mini-plugs. Segmentation of the registered tomograms and their differences facilitated estimation of the residual oil saturation. These predictions from digital analysis agreed reasonably well with laboratory measurements of oil saturation from extraction of sister mini-plugs and spectrophotometry. The tomogram segmentations provide additional information beyond this average value, such as the fractions of oil associated with macroporosity and microporosity. After the tomogram acquisitions, one of the dried mini-plugs was cut and SEM imaged at this exposed face to provide 2D images of fine features below the micro-CT resolution limit, such as the characteristic dimpled texture of asphaltene films on calcite surfaces due to their local wettability alteration in the reservoir. A new registration procedure was developed to embed the SEM images from the cut plug into the tomogram of the original uncut plug at their correct locations, so that this high-resolution wettability information could be integrated into the 3D pore network description and correlated to the local distribution of residual oil. Introduction Although waterflooding has been used for decades to recover oil, the recovery mechanisms at the pore- and molecular-scales remain uncertain. Two poorly characterized and interrelated factors are thought to control multiphase flow in rocks. One is the pore-scale configuration of the fluids and their interfaces within the complex geometry and topology of the pore space. The other is the wettability, which is dictated by the crude oil/brine/rock interactions resulting from the molecular-scale surface chemistry (Salathiel 1973; Anderson 1986; Morrow 1990). Developments in 3D imaging by X-ray computed micro-tomography (micro-CT) and image processing and analysis have been harnessed to visualize and quantify pore networks in rocks (Sheppard et al. 2005), and more recently to image their partial occupancy by two immiscible fluids. Wet-state imaging typically necessitates the doping of one of the two fluids to accentuate its X-ray attenuation, e.g., by dosing the oil with a heavy halogenated analog or the brine with a heavy salt. Such approaches have been used to map the pore-scale saturation in rocks prepared in a sequence of states (Seright et al. 2006), for which tomogram registration algorithms (Latham et al. 2008) are invaluable to monitor changes in individual pores (Kumar et al. 2009). Recent applications to flow (Blunt et al. 2012) and flooding (Wildenschild and Sheppard, 2013) have led to enhanced insight into pore-scale mechanisms and offer the opportunity to explain trends and uncertainties in laboratory measurements and to calibrate computational models of recovery.

Abstract Detection and examination of fluid inclusions can lead to insight into diagenesis and history of a hydrocarbon reservoir. Currently, geologists are faced with a large collection of digital images, making manual investigation highly inefficient and time-consuming. A combination of data acquisition by simple and robust light microscopy and an advanced downstream computational solution is ideal with respect to cost efficiency and stable large-scale and high-throughput ability. Moreover, a strict deterministic algorithm for automatic fluid inclusion detection is not subjected to any human biases that would otherwise violate detection consistency. A novel algorithm for fluid inclusion detection has been developed and implemented in the statistical scripting language R and the object-oriented programming language C# under the .NET 4.0 computational framework. The algorithm is a result of thorough understanding of the image representation of fluid inclusions and optimized based on empirical correlations. It is based on sequential image section-specific intensity-centric selection criteria, intensity distribution discrimination and conditional statistics. Moreover, a multi-dimensional scoring-scheme has been developed and implemented. The software was able to successfully identify a series of fluid inclusions on the same thin-section image containing hydrocarbon and aqueous phases, respectively. Due to the modular structure the software is highly flexible and can be tailor-made to specific analytical needs, such as selective identification of solid phases. Introduction Fluid inclusions are present as chemical impurities in virtually all crystals. A fluid inclusion is a microscopic sample of fluid (liquid or gas) that is trapped within a crystal (10–40mm), as shown in Figure 1, preserving a record of the physico-chemical conditions prevalent during the crystal growth. Detailed fluid inclusion examinations, in conjunction with classical petrography and geochemical work, are therefore important to help unravel the diagenetic history of e.g. cements that plug pores and reduce the permeability of reservoir rocks. Calcite and anhydrite cement crystals present in reservoir rocks have been shown to contain fluid inclusions that provide data on the nature, composition, temperature and density of the fluids present during diagenesis and hydrocarbon charge.

Abstract The majority of alkali-surfactant-polymer (ASP) applications to date have targeted medium-to-high permeability sandstone reservoirs containing reservoir brine with moderate salinity and hardness. Surfactant flooding experiments have been reported in carbonates, but applications targeting oil-wet, low-permeability limestone rock are still uncommon. This paper contains results from laboratory core flood tests performed on an oil-wet limestone rock from the Al Shaheen field, offshore Qatar. The rock samples investigated had approximately 30% porosity and 5 mD permeability, whereas the reservoir brine had a salinity of about 120,000 ppm of which about 10,000 ppm were divalent cations. The first screening step involved testing combinations of several commercial surfactants, co-surfactant and alkalis. Two cost-effective surfactant systems were identified. The first system, denoted ITR, was capable of reducing the interfacial tension below 0.001 mN/m over the required range of salinities. The second system, referred to as WA, effectively altered the wettability from strongly oil-wet to intermediate-wet. Static adsorption was measured to be low for both systems. No polymer was used because the permeability was very low. Both surfactant systems yielded significant incremental oil, when injected in tertiary as well as in secondary mode. The ITR system recovered almost 95% of OIIP but required many pore volumes since the cores remained oil-wet. The WA system, on the other hand, recovered some 85% of OIIP in secondary mode but achieved this with much fewer pore volumes. The WA system was subjected to extensive analysis. Relative permeability curves from unsteady-state core flooding data were derived and experiments were simulated with UTCHEM. The main conclusion from the extensive laboratory work is that surfactant systems can be tailored to recover a significant amount of oil from a low-permeability carbonate reservoir. Wettability alteration may assist in unlocking significant volumes of additional oil from this complex, offshore field.