Rosalind Archer

Wind Turbine Interference in a Wind Farm Layout Optimization Mixed Integer Linear Programming Model

This work develops a wind intensity interference coefficient which captures the interference caused by an upwind turbine on a downwind turbine in the same wind flow. This coefficient includes the use of a Weibull distribution to handle variability in the wind velocity, and also accounts for the geometric relationship between the turbines and the boundaries of the wind sector. This interference coefficient then forms part of a mixed integer linear program (MILP) which is used to optimise the locations of wind turbines within a wind farm site. The MILP approach is an exact method that can guarantee that the turbine locations determined by the model are optimal with respect to an a priori chosen set of possible turbine locations. Tests on an example data set (based on a demonstration case in the WindFarmer software) show, for the particular wind resource used, that interference results in a loss of power of approximately 4.2% when compared to the power production which would be predicted without accounting for interference.

Improving recovery from mature oil fields producing from carbonate reservoirs: Upper Jurassic Smackover Formation, Womack Hill field (eastern Gulf Coast, U.S.A.)

Reservoir characterization, modeling, and simulation were undertaken to improve production from Womack Hill field (eastern Gulf Coast, United States). This field produces oil from Upper Jurassic Smackover carbonate shoal reservoirs. These reservoirs occur in vertically stacked, heterogeneous depositional and porosity cycles. The cycles consist of lime mudstone and wackestone at the base and ooid grainstone at the top. Porosity has been enhanced through dissolution and dolomitization. Porosity is chiefly interparticle, solution-enlarged interparticle, grain moldic, intercrystalline dolomite, and vuggy pores. Dolostone pore systems and flow units have the highest reservoir potential. Petroleum-trapping mechanisms include a fault trap (footwall uplift with closure to the south against a major west-southeast–trending normal fault) in the western area, a footwall uplift trap associated with a possible southwest-northeast–trending normal fault in the south-central area, and a salt-cored anticline with four-way dip closure in the eastern area. Potential barriers to flow are present as a result of petrophysical differences among and within the cycles, as well as the presence of normal faulting. Reservoir performance analysis and simulation indicate that the unitized western area has less than 1 MMSTB of oil remaining to be recovered, and that the eastern area has 2–3 MMSTB of oil to be recovered. A field-scale reservoir management strategy that includes the drilling of infill wells in the eastern area of the field and perforating existing wells in stratigraphically higher porosity zones in the unitized western area is recommended for sustaining production from the Womack Hill field.

Numerical metrics for automated quantification of interstitial cell of Cajal network structural properties

Depletion of interstitial cells of Cajal (ICC) networks is known to occur in several gastrointestinal motility disorders. Although confocal microscopy can effectively image and visualize the spatial distribution of ICC networks, current descriptors of ICC depletion are limited to cell numbers and volume computations. Spatial changes in ICC network structural properties have not been quantified. Given that ICC generate electrical signals, the organization of a network may also affect physiology. In this study, six numerical metrics were formulated to automatically determine complex ICC network structural properties from confocal images: density, thickness, hole size, contact ratio, connectivity and anisotropy. These metrics were validated and applied in proof-of-concept studies to quantitatively determine jejunal ICC network changes in mouse models with decreased (5-HT2B receptor knockout (KO)) and normal (Ano1 KO) ICC numbers, and during post-natal network maturation. Results revealed a novel remodelling phenomenon occurring during ICC depletion, namely a spatial rearrangement of ICC and the preferential longitudinal alignment. In the post-natal networks, an apparent pruning of the ICC network was demonstrated. The metrics developed here enabled the first detailed quantitative analyses of structural changes that may occur in ICC networks during depletion and development.

Energetics of normal earthquakes on dip-slip faults

That earthquakes release vast quantities of energy is widely accepted; however, the most commonly experienced component, radiated seismic energy, is a minor contribution to the total energy budget. The elastic rebound model for earthquakes recognizes that elastic strain energy does work displacing, deforming, and accelerating the crust, as well as causing frictional heating. In this paper we present an energy budget for dip-slip fault rupture in an extensional tectonic regime. A computational model of an elastic-plastic-viscous crust hosting a single fault, modeled as two surfaces in frictional contact, demonstrates contrasting energy flows between the hanging-wall and footwall fault blocks. Our analysis suggests that in the period leading up to an earthquake, the total strain energy contained within the crust decreases, although a local increase within the footwall at mid-crustal depths is observed. During an earthquake, the footwall is subject to an elastic rebound, whereupon uplift of the fault scarp is caused by a mid-crustal stress drop and elastic expansion that releases strain energy. In contrast, gravitational potential energy released from a subsiding hanging wall does work compressing the wider crust, particularly in the mid-crust at the fault tip. This has the unusual consequence of increasing strain energy throughout much of the upper crust during an earthquake. These counterintuitive energy flows suggest that extensional deformation is caused by stored gravitational potential and elastic strain energy, and not by the external tectonic forcing.

A Stochastic Multi-Scale Model of Electrical Function in Normal and Depleted ICC Networks

Multi-scale modeling has become a productive strategy for quantifying interstitial cells of Cajal (ICC) network structure-function relationships, but the lack of large-scale ICC network imaging data currently limits modeling progress. The single normal equation simulation (SNESIM) algorithm was utilized to generate realistic virtual images of small real wild-type (WT) and 5-HT2B-receptor knockout (Htr2b)-/-) mice ICC networks. Two metrics were developed to validate the performance of the algorithm: 1) network density, which is the proportion of ICC in the tissue; and 2) connectivity, which reflects the degree of connectivity of the ICC network. Following validation, the SNESIM algorithm was modified to allow variation in the degree of ICC network depletion. ICC networks from a range of depletion severities were generated, and the electrical activity over these networks was simulated. The virtual ICC networks generated by the original SNESIM algorithm were similar to that of their real counterparts. The electrical activity simulations showed that the maximum current density magnitude increased as the network density increased. In conclusion, the SNESIM algorithm is an effective tool for generating realistic virtual ICC networks. The modified SNESIM algorithm can be used with simulation techniques to quantify the physiological consequences of ICC network depletion at various physical scales.

The effect of luminal content and rate of occlusion on the interpretation of colonic manometry

Background  Manometry is commonly used for diagnosis of esophageal and anorectal motility disorders. In the colon, manometry is a useful tool, but clinical application remains uncertain. This uncertainty is partly based on the belief that manometry cannot reliably detect non‐occluding colonic contractions and, therefore, cannot identify reliable markers of dysmotility. This study tests the ability of manometry to record pressure signals in response to non‐lumen‐occluding changes in diameter, at different rates of wall movement and with content of different viscosities.

Cellular automaton model for simulating tissue-specific intestinal electrophysiological activity

Depletion of interstitial cell of Cajal (ICC) networks is known to occur in various gastrointestinal (GI) motility disorders. Although techniques for quantifying the structure of ICC networks are available, the ICC network structure-function relationships are yet to be well elucidated. Existing methods of relating ICC structure to function are computationally expensive, and it is difficult to up-scale them to larger multiscale simulations. A new cellular automaton model for simulating tissue-specific slow wave propagation was developed, and in preliminary studies the automaton model was applied on jejunal ICC network structures from wild-type and 5-HT2B receptor knockout (ICC depleted) mice. Two metrics were also developed to quantify the simulated propagation patterns: 1) ICC and 2) non-ICC activation lag metrics. These metrics measured the average delay in time taken for the slow wave to propagate across the ICC and non-ICC domain throughout the entire network compared to the theoretical fastest propagation, respectively. Slow wave propagation was successfully simulated across the ICC networks with greatly reduced computational time compared to previous methods, and the propagation pattern metrics quantitatively revealed an impaired propagation during ICC depletion. In conclusion, the developed slow wave propagation model and propagation pattern metrics offer a computationally efficient framework for relating ICC structure to function. These tools can now be further applied to define ICC structure-function relationships across various spatial and temporal scales.

A Discrete Fracture Network Approach to Conditioning Petroleum Reservoir Models Using Seismic Anisotropy and Production Dynamic Data

This paper demonstrates an integrated approach to conditioning models for fractured petroleum reservoirs, through application of discrete fracture network ( DFN) methods. The approach is built on the observation that discrete fractures controlling reservoir production can also influence the anisotropy of seismic response. The paper extends previous work by the above authors by considering realistic fractured reservoir geometries including multiple fracture sets. The presence of a system of natural fractures in a reservoir induces anisotropy in its hydraulic and elastic properties. Fracture induced hydraulic anisotropy and related heterogeneous connectivity is evidenced through systematic non- uniform production performance. Elastic anisotropy may be observed in seismic data as azimuthally dependent elastic attributes such as compressional wave velocity and reflection amplitude versus azimuth which may be inverted from 3D seismic data. Previous work by the above authors demonstrated a method for simultaneous inversion of production and seismic observations through a gradient- based optimization scheme. I n that work, the improvement in conditioning of the DFN model was demonstrated in a synthetic case containing a single fracture set. The current work builds on previous work by the authors through application of the new method to reservoirs containing two fracture systems. The robustness of the method with respect to host rock type is tested through use of matrix petrophysical and elastic properties representative of typical fractured reservoir lithologies. DFN model preconditioning requirements are explored through sensitivity testing with respect to hydraulic, elastic, and geometrical model parameters. The added value of seismic anisotropy in the inversion is demonstrated through comparison with a similar inversion process using only production data in the obj ective function. The results show that the new method for integration of production and seismic anisotropy provides improvement in resolution of the geometrical properties of multiple fracture systems over that which is achievable using production observations alone. The speed and stability of model convergence using the new process is dependent upon both fracture network and host rock properties. Key issues in model preconditioning observed in sensitivity tests are discussed.

A mixed finite element solver for natural convection in porous media using automated solution techniques

IntroductionNatural convection in porous media is an important subject with applications in many geophysical and engineering fields, such as CO2 sequestration in brine aquifers. Numerical modeling plays an important role in understanding the dynamics of these flows and making suitable decisions. However, the traditional process of developing numerical solvers is time-consuming and error-prone. ObjectivesThis paper aims to present the design, implementation and verification of a fully coupled finite element solver for the simulation of natural convection in porous media, by making use of automated solution techniques. MethodsThe mathematical model is composed of the mass conservation equation for fluid flow, Darcys law to relate pressure and velocity, and the advection-diffusion equation for the temperature/concentration field. In order to discretize the system of equations, a mixed finite element pair, namely a Brezzi-Douglas-Marini element and a discontinuous Galerkin element, is used to interpolate the velocity and the pressure field, respectively, while a discontinuous Galerkin element is chosen for the temperature/concentration. With the help of automated solution techniques, a readable and extensible code is developed for this class of multiphysics problems. The code is developed with FEniCS, an open-source framework for the automated solution of partial differential equations through the finite element method. ResultsAfter a convergence test using the method of manufactured solutions, the developed solver is validated by comparing the numerical results against commonly cited benchmarks. In all cases, results in this work are in good agreement with the benchmarks. ConclusionThe test results demonstrate the correctness of the implementation and the effectiveness of automated solution techniques for model development. HighlightsImplementation with the automated FE framework FEniCS.Verification and convergence test through the method of manufactured solutions.Validation with extensive benchmark problems drawn from the literature.Complete source code is available online.

A Stochastic Algorithm for Generating Realistic Virtual Interstitial Cell of Cajal Networks

Interstitial cells of Cajal (ICC) play a central role in coordinating normal gastrointestinal (GI) motility. Depletion of ICC numbers and network integrity contributes to major functional GI motility disorders. However, the mechanisms relating ICC structure to GI function and dysfunction remains unclear, partly because there is a lack of large-scale ICC network imaging data across a spectrum of depletion levels to guide models. Experimental imaging of these large-scale networks remains challenging because of technical constraints, and hence, we propose the generation of realistic virtual ICC networks in silico using the single normal equation simulation (SNESIM) algorithm. ICC network imaging data obtained from wild-type (normal) and 5-HT2B serotonin receptor knockout (depleted ICC) mice were used to inform the algorithm, and the virtual networks generated were assessed using ICC network structural metrics and biophysically-based computational modeling. When the virtual networks were compared to the original networks, there was less than 10% error for four out of five structural metrics and all four functional measures. The SNESIM algorithm was then modified to enable the generation of ICC networks across a spectrum of depletion levels, and as a proof-of-concept, virtual networks were successfully generated with a range of structural and functional properties. The SNESIM and modified SNESIM algorithms, therefore, offer an alternative strategy for obtaining the large-scale ICC network imaging data across a spectrum of depletion levels. These models can be applied to accurately inform the physiological consequences of ICC depletion.