Quantifying Phase Configuration Inside an Intact Core Based on Wettability Using X-ray Computed Tomography

The ability to evaluate rock and fluid properties on the order of a few microns opens new areas in reservoir engineering and reservoir simulation. Multiple studies have been done on the application of x-ray computed tomography (microCT) for the pore-scale evaluation of fluid interfaces and rock-fluid interaction. A majority of the fluid flow governing interactions occur at the pore scale level and is usually overseen on large reservoir scales. Hence, it is important to carefully investigate such interactions. Multi-fluid-phase distribution and interaction of two immiscible fluids such as oil and water is one of the most important and constantly investigated subjects in the oil and gas industry. Oil-water interaction is a complex phenomenon governed by various flow mechanisms in addition to fluid and rock physical properties. Wettability is one of the major concepts of the fluid flow through the porous media and a physical property of the rock that influences hydrocarbon recovery and the recovery methods. Oil and water phase distribution and residual blob configurations in water-wet and oil-wet Berea sandstone cores were successfully identified using x-ray computed tomography. Residual and remaining oil saturations were calculated from the obtained images. Rock porosity was calculated using indicator kriging segmentation technique and fluid saturations were calculated using watershed segmentation. Residual oil blob geometry in the water-wet core was successfully obtained from the segmented images. Oil saturations and phase configurations were in agreement with the oil saturation estimations obtained through the capillary desaturation analysis

Transient Study of the Wetting Films in Porous Media Using 3D X-Ray Computed Micro-Tomography: Effect of Imbibition Rate and Pore Geometry

Imbibition in porous media is governed by the complex interplay between viscous and capillary forces, pore structure and fluid properties. Understanding and predicting imbibition is important in many natural and engineered applications; it affects the efficiency of oil production operations, the moisture and contaminant transport in soil science, and the formation of defects in certain types of composite materials. Majority of the studies published on the transient imbibition behavior in a porous medium were conducted in the simplified 2D transparent micromodels or the 2D projection visualization (X-ray or visible light) of the 3D porous medium. However, the pore level transient imbibition studies have not been reported on real three dimensional porous medium. The main challenge arises from the slowness of the present 3D imaging techniques in comparison with the speed of the pore filling events. To overcome these difficulties, we have developed a novel experimental technique using UV-induced polymerization, which allows the fluid phase distributions to be frozen in place during transient imbibition. Pore-scale structure of the front can then be examined in the 3D microscopic details using the X-ray Computed micro-Tomography (XCT). We have also developed a suite of advanced image segmentation programs to segment the grayscale XCT data. Image-based physically representative pore network generation techniques were unitized to quantify the geometry and topology of pore, wetting and nonwetting phase structure. Using UV initiated polymerization technique and image-based quantitative analysis tools; we have studied the effects of capillary number, pore structure and surface roughness on the structure of the transient imbibition front

Pore-Scale Analysis of DNAPL Dissolution and Biomass Distribution

A comparison of equilibrium and non-equilibrium dissolution of tetrachloroethylene (PCE) was conducted to ascertain how PCE saturation, individual blob properties (volume, surface area, sphericity), and PCE occupied pores are affected by two distinct dissolution regimes. One-dimensional columns were imaged at various dissolution stages using high resolution (~10 um) synchrotron x-ray tomography (XT) and image subvolumes were analyzed using a series of grain, pore network structure, and blob analysis algorithms. An analysis of algorithm-generated data was conducted to determine grain and pore statistics, PCE saturation and individual blob properties, and correlations between PCE blobs and pore network structure. Grain and pore data demonstrated an accurate and consistent segmentation of grains and pores across experiments and a consistent packing between columns. PCE removal rates with pore volumes flushed in both equilibrium and nonequilibrium experiments were consistent until arrival of the primary dissolution front in equilibrium columns. Arrival of the primary dissolution front and number of pore volumes required to completely remove PCE from equilibrium experiments matched well with theoretical predictions. Nonequilibrium dissolution rates varied during the course of the experiment, with increased dissolution observed near the conclusion of the experiments. Blob properties within the equilibrium columns remained relatively constant for all dissolution steps prior to the arrival of the primary dissolution front. Changes in pore-level blob properties in the nonequilibrium experiments were correlated to small perturbations in the mass transfer rates. Deviations in mass transfer rates within the subvolumes occurred over relatively short timescales and are most likely due to the inability to image and analyze a representative elementary volume (REV). XT was also used to investigate the feasibility of imaging biomass within a porous media system. Lugol’s iodine was used to dope the biomass and mass attenuation histograms were compared to those of an undoped biomass system and an abiotic system imaged with and without Lugol’s iodine filling the pore space. After pre-processing with an anisotropic diffusion program, the biomass could be identified within void space of the biotic columns. This insight will aid in the development of XT in exploring the effects of biomass on pore-scale aqueous flow paths

Benthic mapping of the Bluefields Bay fish sanctuary, Jamaica

Small island states, such as those in the Caribbean, are dependent on the nearshore marine ecosystem complex and its resources; the goods and services provided by seagrass and coral reef for example, are particularly indispensable to the tourism and fishing industries. In recognition of their valuable contributions and in an effort to promote sustainable use of marine resources, some nearshore areas have been designated as fish sanctuaries, as well as marine parks and protected areas. In order to effectively manage these coastal zones, a spatial basis is vital to understanding the ecological dynamics and ultimately inform management practices. However, the current extent of habitats within designated sanctuaries across Jamaica are currently unknown and owing to this, the Government of Jamaica is desirous of mapping the benthic features in these areas. Given the several habitat mapping methodologies that exist, it was deemed necessary to test the practicality of applying two remote sensing methods - optical and acoustic - at a pilot site in western Jamaica, the Bluefields Bay fish sanctuary. The optical remote sensing method involved a pixel-based supervised classification of two available multispectral images (WorldView-2 and GeoEye-1), whilst the acoustic method comprised a sonar survey using a BioSonics DT-X Portable Echosounder and subsequent indicator kriging interpolation in order to create continuous benthic surfaces. Image classification resulted in the mapping of three benthic classes, namely submerged vegetation, bare substrate and coral reef, with an overall map accuracy of 89.9% for WorldView-2 and 86.8% for GeoEye-1 imagery. These accuracies surpassed those of the acoustic classification method, which attained 76.6% accuracy for vegetation presence, and 53.5% for bottom substrate (silt, sand and coral reef/ hard bottom). Both approaches confirmed that the Bluefields Bay is dominated by submerged aquatic vegetation, with contrastingly smaller areas of bare sediment and coral reef patches. Additionally, the sonar revealed that silty substrate exists along the shoreline, whilst sand is found further offshore. Ultimately, the methods employed in this study were compared and although it was found that satellite image classification was perhaps the most cost-effective and well-suited for Jamaica given current available equipment and expertise, it is acknowledged that acoustic technology offers greater thematic detail required by a number of stakeholders and is capable of operating in turbid waters and cloud covered environments ill-suited for image classification. On the contrary, a major consideration for the acoustic classification process is the interpolation of processed data; this step gives rise to a number of potential limitations, such as those associated with the choice of interpolation algorithm, available software and expertise. The choice in mapping approach, as well as the survey design and processing steps is not an easy task; however the results of this study highlight the various benefits and shortcomings of implementing optical and acoustic classification approaches in Jamaica.Persons automatically associate tropical waters with spectacular views of coral reefs and colourful fish; however many are perhaps not aware that these coral reefs, as well as other living organisms inhabiting the seabed are in fact extremely valuable to our existence. Healthy coral reefs and seagrass assist in maintaining the sand on our beaches and fish populations and are thereby crucial to the tourism and fishing industries in the Caribbean. For this reason, a number of areas are protected by law and have been designated fish sanctuaries or marine protected areas. In order to understand the functioning of theses areas and effectively inform management strategy, the configuration of what exists on the seafloor is crucial. In the same vein that a motorist needs a road map to navigate unknown areas, coastal stakeholders require maps of the seafloor in order to understand what is happening beneath the water’s surface. The location of seafloor habitats within fish sanctuaries in Jamaica are currently unknown and the Government is interested in mapping them. However a myriad of methods exist that could be employed to achieve this goal. Remote sensing is a broad grouping of methods that involve collecting information about an object without being in direct physical contact with it. Many researchers have successfully mapped marine areas using these techniques and it was believed crucial to test the practicality of two such methods, specifically optical and acoustic remote sensing. The main question to be answered from this study was therefore: Which mapping approach is better for benthic habitat mapping in Jamaica and possibly the wider Caribbean? Optical remote sensing relates to the interaction of energy with the Earth’s surface. A digital photograph is taken from a satellite and subsequently interpreted. Acoustic/ sonar technology involves the recording of waveforms reflected from the seabed. Both methods were employed at a pilot site, the Bluefields Bay fish sanctuary, situated in western Jamaica. The optical remote sensing method involved the classification of two satellite images (named WorldView-2 and GeoEye-1) and this process was informed using known positions of seafloor features, this being known as supervised image classification. With regard to the acoustic method, a field survey utilising sonar equipment (BioSonics DT-X Portable Echosounder) was undertaken in order to collect the necessary sonar data. The processed field data was modelled in order to convert lines of field point data to one continuous map of the sanctuary, a process known as interpolation. The accuracy of each method was then tested using field knowledge of what exists in the sanctuary. The map resulting from the image classification revealed three seafloor types, namely submerged vegetation, coral reef and bare seafloor. The overall map accuracy was 89.9% for the WorldView-2 image and 86.8% for GeoEye-1 imagery. These accuracies surpassed those attained from the acoustic classification method (76.6% for vegetation presence and 53.5% for bottom type - silt, sand and coral reef/ hard bottom). Similar to previous studies undertaken, it was shown that the seabed of Bluefields Bay is primarily inhabited by submerged aquatic vegetation (including seagrass and algae), with contrastingly smaller areas of bare sediment and coral reef. Ultimately, the methods employed in this study were compared and the pros and cons of each were weighed in order to deem one method more suitable in Jamaica. Often, the presence of cloud and suspended matter in the water block the view of the seafloor making image classification difficult. On the contrary, acoustic surveys are capable of operating throughout cloudy conditions and attaining more detailed information of the ocean floor, otherwise not possible with optical remote sensing. A major step in the acoustic classification process however, was the interpolation of processed data, which may introduce additional limitations if careful consideration is not given to the intricacies of the process. Lastly, the acoustic survey certainly required greater financial resources than satellite image classification. In answer to the main question of this study, the most cost effective and feasible mapping method for Jamaica is satellite image classification (based on the results attained). It must be stressed however that the effective implementation of any method will depend on a number of factors, such as available software, equipment, expertise and user needs, that must be weighed in order to select the most feasible mapping method for a particular site

Unsupervised segmentation evaluation measures for parameter optimization in indicator-Kriging

This work investigates the performance of four unsupervised evaluation measures for the optimization of the user-defined parameter in the indicator-Kriging segmentation algorithm (Oh and Lindquist 1999). We focus on the application of this algorithm to micro-computed tomography (µCT) scans of porous media. Because ground truth segmentations were required for the set of test images, simulated 3D images were created based on the image acquisition in µCT, starting from segmentations of real µCT-scans. The tested unsupervised evaluation measures were the intra-class variance, Otsu's parameter, Zeboudj's parameter and the grey value contrast. The intra-class variance proved to be the most efficient at selecting an optimal segmentation parameter

Deriving probabilistic short-range forecasts from a deterministic high-resolution model

In order to take full advantage of short-range forecasts from deterministic high-resolution NWP models, the direct model output must be addressed in a probabilistic framework. A promising approach is mesoscale ensemble prediction. However, its operational use is still hampered by conceptual deficiencies and large computational costs. This study tackles two relevant issues: (1) the representation of model-related forecast uncertainty in mesoscale ensemble prediction systems and (2) the development of post-processing procedures that retrieve additional probabilistic information from a single model simulation. Special emphasis is laid on mesoscale forecast uncertainty of summer precipitation and 2m-temperature in Europe. Source of forecast guidance is the deterministic high-resolution model Lokal-Modell (LM) of the German Weather Service. This study gains more insight into the effect and usefulness of stochastic parametrisation schemes in the representation of short-range forecast uncertainty. A stochastic parametrisation scheme is implemented into the LM in an attempt to simulate the stochastic effect of sub-grid scale processes. Experimental ensembles show that the scheme has a substantial effect on the forecast of precipitation amount. However, objective verification reveals that the ensemble does not attain better forecast goodness than a single LM simulation. Urgent issues for future research are identified. In the context of statistical post-processing, two schemes are designed: the neighbourhood method and wavelet smoothing. Both approaches fall under the framework of estimating a large array of statistical parameters on the basis of a single realisation on each parameter. The neighbourhood method is based on the notion of spatio-temporal ergodicity including explicit corrections for enhanced predictability from topographic forcing. The neighbourhood method derives estimates of quantiles, exceedance probabilities and expected values at each grid point of the LM. If the post-processed precipitation forecast is formulated in terms of probabilities or quantiles, it attains clear superiority in comparison to the raw model output. Wavelet smoothing originates from the field of image denoising and includes concepts of multiresolution analysis and non-parametric regression. In this study, the method is used to produce estimates of the expected value, but it may be easily extended to the additional estimation of exceedance probabilities. Wavelet smoothing is not only computationally more efficient than the neighbourhood method, but automatically adapts the amount of spatial smoothing to local properties of the underlying data. The method apparently detects deterministically predictable temperature patterns on the basis of statistical guidance only