The stratigraphic response to marine shoreline transgressions have been debated for the last six decades. A particularly interesting aspect is that transgressive ravinement often removes evidence of the shoreline itself, until there is turnaround to regression. To elucidate this topic, we present a high-resolution chronostratigraphic study of an overall transgressive coastline, documented with evidence from over 1450 wells covering an area of 6200 km 2 to define the fundamental sandbodies and relevant stratigraphic surfaces. The mapping of 15 elongate sandstone units stacked into 6 reservoirs shows that there was a spectacular westward rising of back-stepping barrier spits, sourced by long-shore currents mobilizing sand from a delta to the north. Each fundamental barrier spit unit (BSU) is a 6-12 metres thick, regressive, southward elongate and narrowing sandbody generated by longshore drift of sandy sediment. Each barrier sand body and its related overlying transgression is estimated to represent some 20 Ky. Strong transgressive ravinement events periodically flooded the barrier spits and shifted the deposition westward in four to 35 km steps. Westward transgressive-stepping across and into a structurally-generated embayment progressively dampened wave energy with each backstep. Morphologically, there were two endmember sandbody types: 1) narrow, drum stick-like sandbodies built mostly by longshore accretion, i.e. true barrier bars, and 2) broader and more extensive regressive belts of sandstone that resemble strandplains. The former display typically longer backsteps across lagoonal areas whereas the latter show a more aggradational stacking arrangement which evidences a quasi-balance between accommodation and sediment supply. There is no evidence of a smooth and continuous transgression controlling sandstone deposition and preservation. A hybrid punctuated transgression model, that considers the alternation of long-term coastal retrogradation and short-lived barrier spit development by longshore accretion and seaward progradation, is the most appropriate model for creating and preserving Upper Almond sandbodies.

Understanding the linkages between grain mineralogy and diagenetic and sedimentary processes enhances the reliability of petrophysical models to predict reservoir deliverability from permeability. Petrographic data within well-defined depositional facies reveal the diagenetic evolution of porosity-permeability relationships. Formation evaluation methods relying solely on petrophysical rock typing are seriously limited when predicting ultimate reservoir performance in complex pore structures. The Almond Formation, Wyoming, is characterized by three depositional facies associations — shoreface, deltaic (bay head and flood tide), and fluvial-coastal plain — which present three distinctive porosity-permeability trends. Textural features resulting from depositional processes, such as grain size and sorting, vary little between facies associations, yet permeability can vary by up to four orders of magnitude for the same porosity value. Differences between petrophysical facies are primarily driven by diagenetic (cementation and grain dissolution) effects on different framework grain compositions (petrographic facies). Therefore, the main difference between the facies associations is diagenetic, due to provenance and transport mechanisms. The characterization of depositional and diagenetic controls on pore geometry allows the narrowing of uncertainty in absolute permeability prediction. We have quantified the relationship between depositional facies, with their specific mineral composition and diagenetic overprint, and the steepness functions in porosity-permeability space. This analysis allowed us to effectively reduce the uncertainty in the prediction of initial gas production from wireline logs.

Tight-gas reservoirs undergo unique and often complex burial, diagenetic, structural, fluid pressure and saturation histories. Porosity alteration from compaction, cementation and grain leaching can continue after hydrocarbon charge, further complicating saturation modeling. Many reservoirs have gone through multiple cycles of drainage and imbibition, often at different stages on the diagenetic pathway to current pore-scale morphologies. The understanding of saturation distribution and state is not only desired but required for predicting reservoir performance, estimating realistic recoverable volumes, and optimizing costs for development and production.The Almond Formation is characterized by three depositional facies associations: shoreface, deltaic and fluvial-coastal plain. These groups are commonly fine grained and well sorted. The differences in pore architecture arise from differences in primary depositional fabric and rock-frame mineralogy and their subsequent diagenetic alteration; yielding predictive trends in porosity permeability space.Drainage and imbibition saturation-height models have been developed from core studies and integrated with logs to verify that reservoirs are at primary drainage and to highlight any potential imbibition due to trap tilting or leaking. Centrifuge and multicycle mercury injection data were integrated to produce composite drainage capillary pressure curves. Stressed mercury extrusion tests are commonly used for modeling water saturation through the imbibition process. These tests display no correlation with rock quality at low capillary pressures. To circumvent these problems, mercury extrusion was integrated with maximum-trapped-gas measurements obtained by countercurrent imbibition experiments.Using the resistivity-derived water saturation model as reference, the free-water level for drainage and imbibition models was optimized by matching saturation height models in reservoirs free of resistivity shoulder bed effects. The accuracy of the match in different rock qualities provided insights on the likely saturation state of reservoirs. Such observations were used to develop successful interpretations of the special distribution of free-water level, reservoir architecture, and hydrocarbon charge.

A new method is developed based on streamlines to determine the reservoir properties from formation-tester measurements. To do so, a previously developed finite-difference reservoir model is coupled with a streamline method to simulate the near-wellbore dynamic measurements in the presence of invasion and arbitrary fluid distributions. The streamline method is specifically developed to overcome technical challenges in modeling deviated wells in heterogeneous reservoirs efficiently.In this study, synthetic reservoir models are constructed based on measurements acquired in offshore well A with 15 degrees deviation angle. The streamline-based method is then implemented to simulate packer-type formation-tester measurements and to appraise permeability of multi-layer reservoirs. In addition, transient measurements from a focused-sampling probe-type formation tester is modeled with streamline method to estimate relative permeability and anisotropy in offshore well B. Inversion results indicate that the accuracy of estimated formation properties is higher for formations with larger mobility because more streamlines trace flow into probes from large-mobility layers. For offshore well A, in the presence of 5% zero-mean Gaussian additive noise, the uncertainty of permeability varies from 6% to 38% for layers with high and low mobilities, respectively. The uncertainty increases to 8% and 41% for high and low mobility cases, respectively, when 5% skewed-Gaussian noise contaminates the measurements.The coupled finite-difference and streamline-based inversion method (FDSM) is then compared to a previously validated finite-difference reservoir model (FDM). The coupled FDSM is 8 times faster than FDM on an average when estimating properties of heterogeneous reservoirs using inversion on formation-tester measurements acquired in highly deviated wells. Computational advantage of FDSM is due to application of one-dimensional solutions of fluid saturations and concentrations along streamlines instead of three-dimensional FDM numerical calculations. Despite the efficiency, history matching of measurements indicates up to 6% difference between FDSM and FDM in results.In high-angle wells, mud-filtrate invasion causes a non-symmetric distribution of invading fluid around the wellbore perimeter. Moreover, presence of large permeability-porosity contrast among layers increases complexity of numerical computations and uncertainty. This study proposes that the streamline-based inversion method is an excellent candidate to overcome these difficulties efficiently. (C) 2015 Elsevier B.V. All rights reserved.

We have developed a new pore-scale method to quantify petrophysical properties of hydrocarbon (HC)-bearing shale. Recent studies indicate that slip flow, Knudsen diffusion, Langmuir desorption, and diffusion in kerogen contribute to the unconventional production properties of shale-gas formations. Conventional petrophysical interpretation methods do not account for the aforementioned phenomena and are often inconclusive when estimating petrophysical properties in shale formations. We constructed a pore-scale representation of the lower Eagle Ford Shale based on focused-ion-beam–scanning-electron-microscope (FIB-SEM) images. Permeability is calculated via previously developed finite-difference methods for the cases with and without slip flow and Knudsen diffusion. The method also calculates streamlines to describe sample pore connectivity. Weighted throat-size distributions are defined based on streamlines to represent the most resistive paths for fluid flow in the FIB-SEM image. Subsequently, permeability is estimated from the dominant throat size in the weighted throat-size distribution. We used a new fluid percolation model for HC-bearing shale that expands HC from kerogen surfaces and water from grain and clay surfaces into the pore space to vary fluid saturation. Isolated pores are randomly distributed within kerogen to increase kerogen maturity in the model. Electrical resistivity is calculated with a finite-difference solution of Kirchhoff’s voltage law applied at the pore scale. A parallel conductor model was used based on Archie’s equation for water conductivity in pores and a parallel conductive path for the Stern-diffuse layer. Calculations were compared with Waxman-Smits’ and Archie’s predictions of macroscopic electric conductivity. Using practical modeling parameters, the parallel conductor model yields the most accurate prediction of pore-scale sample conductivity for various cases of water saturation and conductivity.

We invoke pore-scale models to evaluate grain shape effects on petrophysical properties of three-dimensional (3D) images from micro-CT scans and consolidated grain packs. Four sets of grain-packs are constructed on the basis of a new sedimentary algorithm with the following shapes: exact angular grain shapes identified from micro-CT scans, ellipsoids fitted to angular grains, and spheres with volume and surface-to-volume ratio equal to original angular grains on a grain-by-grain basis. Subsequently, a geometry-based cementation algorithm implements pore space alteration due to diagenesis. Eight micro-CT scans and 144 grain-pack images with \(500 \times 500 \times 500\) voxels (the resolution units of 3D images) are analyzed in this study. Absolute permeability, formation factor, and capillary pressure are calculated for each 3D image using numerical methods and compared to available core measurements. Angular grain packs give rise to the best agreement with experimental measurements. Cement volume and its spatial distribution in the pore space significantly affect all calculated petrophysical properties. Available empirical permeability correlations for non-spherical grains underestimate permeability between 30 and 70 % for the analyzed samples. Kozeny–Carman’s predictions agree with modeled permeability for spherical grain packs but overestimate permeability for micro-CT images and non-spherical grain packs when volume-based radii are used to calculate the average grain size in a pack. We identify surface-to-volume ratio and grain shape as fundamental physical parameters that control fluid distribution and flow in porous media for equivalent porosity samples.

We introduce a new numerical algorithm to forecast gas production in organic shale that simultaneously takes into account gas diffusion in kerogen, slip flow, Knudsen diffusion, and Langmuir desorption. The algorithm incorporates the effects of slip flow and Knudsen diffusion in apparent permeability, and includes Langmuir desorption as a gas source at kerogen surfaces. We use the diffusion equation to model both lateral gas flow in kerogen as well as gas supply from kerogen to surfaces. Slip flow and Knudsen diffusion account for higher-than-expected permeability in shale-gas formations, while Langmuir desorption maintains pore pressure. Simulations confirm the significance of gas diffusion in kerogen on both gas flow and stored gas. Relative contributions of these flow mechanisms to production are quantified for various cases to rank their importance under practical situations. Results indicate that apparent permeability increases while reservoir pressure decreases. Gas desorption supplies additional gas to pores, thereby maintaining reservoir pressure. However, the rate of gas desorption decreases with time. Gas diffusion enhances production in two ways: it provides gas molecules to kerogen-pore surfaces, hence it maintains the gas desorption rate while kerogen becomes a flow path for gas molecules. For a shale-gas formation with porosity of 5%, apparent permeability of 59.7 μD, total organic carbon of 29%, effective kerogen porosity of 10%, and gas diffusion coefficient of 10 -22 m 2 /s, production enhancements compared to those predicted with conventional models are: 9.6% due to slip flow and Knudsen diffusion, an extra 42.6% due to Langmuir desorption, and an additional 61.7% due to gas diffusion after 1 year of production. The method introduced in this paper for modeling gas flow indicates that the behavior of gas production with time in shale-gas formations could differ significantly from production forecasts performed with conventional models.

We introduce a finite-difference method to simulate pore scale steady-state creeping fluid flow in porous media. First, a geometrical approximation is invoked to describe the interstitial space of grid-based images of porous media. Subsequently, a generalized Laplace equation is derived and solved to calculate fluid pressure and velocity distributions in the interstitial space domain. We use a previously validated lattice-Boltzmann method (LBM) as ground truth for modeling comparison purposes. Our method requires on average 17 % of the CPU time used by LBM to calculate permeability in the same pore-scale distributions. After grid refinement, calculations of permeability performed from velocity distributions converge with both methods, and our modeling results differ within 6 % from those yielded by LBM. However, without grid refinement, permeability calculations differ within 20 % from those yielded by LBM for the case of high-porosity rocks and by as much as 100 % in low-porosity and highly tortuous porous media. We confirm that grid refinement is essential to secure reliable results when modeling fluid flow in porous media. Without grid refinement, permeability results obtained with our modeling method are closer to converged results than those yielded by LBM in low-porosity and highly tortuous media. However, the accuracy of the presented model decreases in pores with elongated cross sections.

Abstract Complex heterogeneous reservoirs penetrated by deviated wells pose significant challenges when modeling and interpreting packer- and probe-type formation-tester measurements. This paper introduces a streamline-based method specifically designed for near-wellbore fluid-flow modeling in vertical and deviated wells. The primary application of the method is for efficient simulation and automatic history matching of formation-tester measurements in the presence of invasion and variable petrophysical and geometrical properties. Based on the spatial distribution of pressure calculated with a previously validated near-wellbore finite-difference model (FDM), the method traces streamlines from the reservoir into fluid sampling probes. The calculated spatial distribution of pressure is input to the streamline-based method to propagate the spatial distribution of water saturation. Subsequently, the calculated spatial distribution of water saturation is input to the FDM to update the spatial distribution of pressure. Streamlines are then recalculated and this repeated pressure-saturation procedure continues until reaching the desired final simulation time. The combined FDM and streamline-based method utilize full-tensor permeability to couple wellbore-reservoir systems during fluid sampling in horizontal and deviated wells. It is shown that the spatial rendering of streamlines permits rapid assessment of the time evolution of fluid saturation near the sampling probe. We successfully test the streamline-based method in the dynamic simulation of fluid contamination into conventional and focused-type probes operating in vertical, horizontal, and deviated wells for the case of multiphase, immiscible fluid-flow in heterogeneous formations. The method implements successive streamline and FDM time steps adaptively to decrease computational time by a factor of four while achieving less than 5% relative difference in the simulation of fluid production measurements when compared to FDM results. For formation testing in deviated wells, the streamline-based method permits more rapid appraisal of anisotropy, bed-boundary, and complex geometrical effects on fluid-sampling times than conventional 3D fluid-flow simulators. It also quantifies the sensitivity of measurements to variations of permeability, invaded zones, anisotropy, and well deviation. Our simulations indicate that fluid sampling in deviated wells subject to mud-filtrate contamination requires adequate positioning of the probe around the perimeter of the wellbore to secure the fasted cleanup possible.

We present an electromigration-aware dynamic routing algorithm, EMARA, for network-on-chip (NoC) applications that has the ability to eliminate the electromigration effects in order to increase the lifetime of SoCs. We formulate the expected lifetime of the NoC system based on the electromigration phenomenon as a function of the bidirectional link load. We introduce the concept of void packet to help in balancing the link load in the case of severe unbalanced condition. We investigate the trade off between the expected system boosted lifetime using EMARA and the network performance measured by average packet latency and power consumption. By utilising bidirectional balanced data transfer, our algorithm increases the expected system's lifetime by two to six orders of magnitude compared with other XY-based dynamic routing algorithms. Simulation results demonstrate that EMARA can achieve more than two orders of magnitude improvement in expected system's lifetime, independently of both traffic pattern and injection rate, with only 1.14% and 4% increase in power consumption and average packet latency, respectively.

Abstract We combine a new pore-scale model with a reservoir simulation algorithm to predict gas production in gas-bearing shales. It includes an iterative verification method of surface mass balance to ensure real-time desorption-adsorption equilibrium with gas production. The pore-scale model quantifies macroscopic petrophysical properties of formations using an algorithm of gas transport in porous media that simultaneously considers the effects of no-slip and slip flow, Knudsen diffusion, and Langmuir desorption. Subsequently, the reservoir model populates petrophysical properties derived from the pore-scale analysis at every numerical grid and at each time-step to calculate the production history and pressure distribution in the reservoir. This approach examines the contribution of different transport processes (i.e. advective flow, Knudsen diffusion, and desorption) to quantify their corresponding contributions to overall flow. Previously, we showed that slip flow and Knudsen diffusion play a significant role in explaining the higher-than-expected permeability observed in shale-gas formations with pore-throat sizes in the range of nanometers. It is shown that Langmuir desorption from organic-matter surfaces is important in the calculation of stored gas in gas-bearing shales. Modeling results show that gas desorption maintains the reservoir pressure via the supply of gas. In comparison to conventional reservoir descriptions, the contributions of slip flow and Knudsen diffusion increase the apparent permeability of the reservoir while gas production takes place. The effects of both mechanisms explain the higher-than-expected gas production rates commonly observed in these formations.

We introduce a new pore·scale method that includes the eflects of no·slip and slip Ilow, Knudsen dill'usion, and Langmuir desorption to model gas flow in porous media. A weighting factor combines the effects of Knudsen diffusion, no·slip, and slip flows in the pore space. Boundary conditions model Langmuir desorption at the surface of grains and organic mailer whi le finite pressures are enforced at the inlet and outlet. Spatial distributions of pressure and fluid velocity in the interstitial domain are calculated using a generalized Laplace equation. Subsequently, apparent penneability is estimated from fluid velocity distributions. Our model is applicable to both conventional and unconventional reservoirs such as carbonates, shale· gas, tight gas and coal·bed methane. Furthennore, the pore-scale simu lation method calculates electrical conductivity of gas-bearing shale in the presence of organic matter, clay bound water, and conductive grains.

Summary. In this paper, we compare predictions of several pore-scale codes for single- and two-phase flow for the first time. Firstly, two implementations of lattice-Boltzmann method (LBM) and a finite-difference based code (FDDA) predict single-phase flow in Fontainebleau sandstone and dolomite samples. We then obtain pore-scale drainage for two fluid phase configurations using a novel level set method based progressive quasi-static (LSMPQS) algorithm for capillarity dominated flow. The resulting fluid configurations are used to compute relative permeability using LBM in each phase as well as formation factor. We demonstrate that the numerical methods compare well with each other and available experimental results.

An analysis is presented of the layer-thickness dependent and temperature-dependent current density in sandwich-type electron-only devices based on the amorphous small-molecule organic semiconductor BAlq, which is frequently used in organic light-emitting diodes. The electron transport can be consistently described by assuming a density of states (DOS) which is a superposition of a Gaussian DOS and an exponential trap DOS, with ∼85 and ∼100meV widths, respectively, using a mobility model which includes the carrier density dependence of the mobility in the Gaussian DOS and assuming either random or spatially correlated site energies. From a comparison of the density of hopping sites obtained from both models and the density of molecules as obtained from chemical analysis, evidence for the presence of correlated disorder is found.

Given the performance and reliability limits of conventional copper interconnects in the tens of nanometer regime, carbon-nanotube (CNT) based interconnects emerge as a potential reliable alternative for future high performance VLSI industry. In this paper, we present an accurate thermally-aware model for single-walled carbon-nanotube (SWCNT) based interconnects. Our thermally-aware model is an integration of temperature-dependent electrical parasitics model and thermal equivalent circuit that captures both self-heating and heat conduction phenomena. We verify the accuracy of our electro-thermal model against recently reported experimental measurements. By leveraging the presented electro-thermal model, we present a simulation platform to estimate the performance of SWCNT-based interconnects under different temperature conditions. Our thermally-aware model achieves improvement in the delay estimation accuracy of about 51.3% on average. Based on our simulation results, SWCNT-based interconnects offer more than 5×reduction in delay at dimensions of about 10–20nm for 27– 127°C temperature range.