ALBERT

Description: Summary A class of monotone cell-centered nonlinear finite-volume methods has been proposed in the past decade to solve the anisotropic diffusion equation. The nonlinear two-point flux approximation (TPFA) (NTPFA) method preserves the nonnegativity of the solution values but can violate the discrete maximum/minimum principle (DMP). To enforce DMP, the nonlinear multipoint flux approximation (NMPFA) method ought to be used. In this work, we propose a novel NTPFA method that can reduce the severity of DMP violations significantly compared with the standard NTPFA method. The new formulation uses conormal decomposition for the construction of the one-sided fluxes. To define the unique flux through a connection between two cells, we choose a convex combination of the two one-sided fluxes such that the absolute differences of the magnitudes of the two transmissibility terms associated with the two neighboring cells are minimized, thus bringing the discrete coefficient matrix closer to having the zero row-sum property. Numerical experiments are conducted to test the performance of the new NTPFA method. The results demonstrate that the new scheme has comparable convergence order for both the solution and the flux compared with the standard NTPFA method or the classical multi-point flux approximation (MPFA-O) method. Moreover, the new NTPFA formulation shows marked improvements over the standard NTPFA in terms of reducing DMP violations. However, depending on the specific problem configuration, our new NTPFA formulation can lead to a system of nonlinear equations that is more difficult to solve.

Description: Summary In this paper, I present numerical results of gas/liquid flows in pipelines obtained from a new simulation code. One difference, with respect to other 1D fluid dynamic commercial simulation products, is the use of a compositional approach to the problem: This is rarely found in published articles about gas/liquid flow in the oil and gas industry. It is shown that the algorithm can calculate both pressure and material fast waves generated during the transportation of gas and liquid in pipes. The solution algorithm is based on the application of a two-fluid model to the mass, momentum, and energy conservation equations, which are solved using a mixed implicit-explicit integration schema. Closure equations for the calculation of interface stress are taken from literature articles. A dam-break simulation (i.e., a Riemann initial value problem) is presented as a severe test case for validation of the two-phase flow algorithm. Because the code is able to capture sharp and fast changes in the liquid holdup connected to the formation of pressure waves, it is applied to the simulation of slug flow without the use of steady-state “unit cell” models and slug tracking functions. In this context, the experimental results on pseudoslug formation in inclined pipes at high pressures, published by the Tulsa University Fluid Flow Project (TUFFP), are used to compare simulated results with experimental data. The last part is dedicated to the simulation of some cases taken from a classical flow-map of a fundamental article by Taitel and Dukler (1976). At constant liquid superficial velocity, the formation of liquid slugs and their subsequent termination with the increase of gas flow rate is simulated with details never previously presented.

Description: Summary Nanoparticles have great potential to mobilize trapped oil in reservoirs because of their chemical, thermal, and interfacial properties. However, the direct application of magnetic forces on superparamagnetic nanoparticles in reservoir engineering applications has not been extensively investigated. We demonstrate the enhanced oil recovery (EOR) potential of hydrophilic superparamagnetic nanoparticles in oil production by direct observation using microfluidics. We studied the mobilization of oil blobs by a ferrofluid (a suspension of hydrophilic superparamagnetic nanoparticles in water) both in a converging/diverging micromodel channel and in a foot-long pore network micromodel, both with varying depth (so-called 2.5D micromodels). The water-based ferrofluid in all cases was the wetting fluid. Initial ferrofluid flooding experiments in single channels were performed without and then with a static magnetic field. This magnetic field caused oil droplet deformation, dynamic breakup into smaller droplets, and subsequent residual oil saturation reduction. During the flooding, after the magnetic field was applied, significant oil displacement was observed within 2 hours [6 pore volumes injected (PVI)], and 86.2% of the oil that was not mobilized without a magnetic field was mobilized within 64 hours (192 PVI). Then, in experiments in the micromodel and in a Hele-Shaw cell without flooding, we observed self-assembly of oil droplets, indicating the formation of the hydrophilic magnetic nanoparticle microstructures (chains under the magnetic field) and their interaction with the oil blobs. Further ferrofluid flooding experiments were performed in a foot-long micromodel under a rotating magnetic field. The oil saturation was reduced from 44.6 to 33.3% after 17 hours (8.5 PVI) of ferrofluid flooding after the rotating magnetic field was applied. Finally, a discussion of field application of ferrofluid flooding is presented.

Description: Summary In this paper, we incorporated a kinematic proppant transport model for spherical suspensions in hydraulic fractures developed by Dontsov and Peirce (2014) in a pseudo-3D hydraulic-fracture simulator for multilayered rocks to capture a different proppant transport speed than fluid flow and abridged fracture channel by highly concentrated suspensions. For pressure-driven proppant transport, the bridges made of compact proppant particles can lead to both proppant distribution discontinuity and increased fracture aperture and height because of the higher pressure. The model is applied to growth of a fracture from a vertical well, which can contain thin-bedded intervals and more than one opened hydraulic-fracture interval, because the fracture plane extends in height through layers with contrasts in stress and material properties. Three numerical examples demonstrate that a loss of vertical connectivity can occur among multiple fracture sections, and proppant particles are transported along the more compliant layers. The proppant migration within a narrow fracture in a thin soft rock layer can result in bridging and formation of a proppant plug that strongly limits fluid speed. This generates an increase of injection pressure associated with fracture screenout, and these screenout events can emerge at different places along the fracture. Next, because of the lack of pretreatment geomechanical data, the values of layer stress and leakoff coefficient are adjusted for a field case so that the varying bottomhole pressure and fracture length are in line with the field measurements. This paper provides a useful illustration for hydraulic-fracturing treatments with proppant transport affected by and interacting with reservoir lithological complexities.

Description: Summary The permeability characteristics of hydrate-bearing reservoirs are critical factors governing gas and water flow during gas hydrate exploitation. Herein, X-ray microcomputed tomography (CT) and the pore network model (PNM) are applied to study the dynamic gas and water relative permeabilities (krg and krw) of hydrate-bearing porous media during the shear process. As such, the dynamic region extraction method of hydrate-bearing porous media under continuous shear is adopted by considering deformation in the vertical direction. The results show that krw and krg of hydrate-bearing porous media are influenced by the effect of disordered sand particle movement under axial strain. Declines in the critical pore structure factors (pore space connectivity, pore size, and throat size) contribute to the reduction in krw and the increase in krg. However, krg decreases during the shear process at a high water saturation (Sw) because of the high threshold pressure and flow channel blockage. In addition, the connate water saturation (Swc) continuously increases during the shear process. Swc is influenced by pore size, throat size, and flow channel blockage. Moreover, the preferential flow direction of krg and krw changes during the continuous shear process. The results of dynamic permeability evolution during the continuous shear process under triaxial stress provide a reference for pore-scale gas and water flow regulation analysis.

Description: Summary Torque and drag models have been used for several decades to calculate tension and torque profiles along drillstrings, casing strings, and liner strings. Buoyancy forces contribute to the loads acting on the pipe and affect its interaction with the borehole wall. Torque and drag calculations account for these localized effects, as well as the material internal forces, torques, and moments on each side of the contact. When the analysis is applied to a discrete length of pipe, the cross sections at each end do not contribute to the buoyancy forces because they are not in contact with the fluid, except where there is a change in diameter or at the end of the string of pipe. We argue that it is important to check that the models used for solid pipe torque and drag calculations remain valid for sand screens, in particular, the extent to which the buoyancy forces acting on a perforated tube might differ from those on a solid pipe. Because the buoyancy force is the result of the pressure gradient acting on the surface of the pipe, the presence of holes may also influence the buoyancy force. We propose that there are theoretical differences between local buoyancy forces acting on plain or perforated tubes. This paper describes how to calculate the local buoyancy force on a portion of a drillstem by the application of Gauss’ theorem and accounting for the necessary corrections arising from the cross sections not being exposed to the fluid. We built an experimental setup to verify that the tension inside a pipe subject to buoyancy behaves in accordance with the derived mathematical analysis. With complex well construction operations, for instance during extended-reach drilling or when drilling very shallow wells with high buildup rates, the slightest error in torques and drag calculations may end up jeopardizing the chances of success of the drilling operation. It is therefore important to check that the basis of design calculations remain valid in those contexts and that, for instance, sand screens or slotted liners may be run in hole safely after a successful drilling operation.

Description: Summary The stimulation of unconventional reservoirs to improve oil productivity in tight formations of shale basins is a key objective in hydraulic fracturing treatments. Such stimulation can be made by reliable fracture fluids that have a high viscosity and elasticity to suspend the proppant in the fracture networks. Recently, due to several operational and economic reasons, the oil industry began using high-viscosity friction reducers (HVFRs) as direct replacements for linear and crosslinked gels. However, some issues can limit the capability of HVFRs to provide effective sand transport, including the high fluid temperature during fracture treatment inside the formations. This may lead to unstable fracture fluids caused by a decrease in the interconnective strength between the fluid chains, which results in reduced viscosity and elasticity. This study comprehensively investigated HVFRs in comparison with guar at various temperatures. An HVFR at 4 gallons per thousand gallons of water (gpt) and guar at 25 pounds per thousand gallons of water (ppt) were selected based on fluid rheology tests and hydraulic fracture execution field results. The rheological measurements of both fracture fluids were conducted at different temperature values (i.e., 25, 50, 75, and 100°C). Static and dynamic proppant settling tests were also conducted at the same temperatures. The results showed that the HVFR provided better proppant transport capability than the guar. The HVFR had better thermal stability than guar, but its viscosity and elasticity decreased significantly when the temperature exceeded 75°C. An HVFR can carry and hold the proppant more deeply inside the fracture than liner gel, but that ability decreases as the temperature increases. Therefore, using conditions that mimic field conditions to measure the fracture fluid rheology, proppant static settling velocity, and proppant dune development under a high temperature is crucial for enhancing the fracture treatment results.

Description: Summary Natural gas hydrate (NGH) is regarded as an important alternative future energy resource. In recent years, a few short-term production tests have been successfully conducted with both permafrost and marine sediments. However, long-term hydrate production performance and the potential geomechanical problems are not very clear. According to the available geological data at the Mallik site, a more realistic hydrate reservoir model that considers the heterogeneity of porosity, permeability, and hydrate saturation was developed and validated by reproducing the field depressurization test. The coupled multiphase and heat flow and geomechanical response induced by depressurization were fully investigated for long-term gas production from the validated hydrate reservoir model. The results indicate that long-term gas production through depressurization from a vertically heterogeneous hydrate reservoir is technically feasible, but the production efficiency is generally modest, with the low average gas production rate of 4.93 × 103 ST m3/d (ST represents the standard conditions) over a 1-year period. The hydrate dissociation region is significantly affected by the reservoir heterogeneity and reveals a heterogeneous dissociation front in the reservoir. The depressurization production results in significant increase of shear stress and vertical compaction in the hydrate reservoir. The response of shear stress indicates that the potential region of sand migration is mainly in the sand-dominant layer during gas production from the hydraulically heterogeneous hydrate reservoir (e.g., sand layers interbedded with clay layers). The maximum subsidence is approximately 78 mm and occurred at the 72nd day, whereas the final subsidence is slowly dropped to 63 mm after 1-year of depressurization production. The vertical subsidence is greatly dependent on the elastic properties and the permeability anisotropy. In particular, the maximum subsidence increased by approximately 81% when the ratio of permeability anisotropy was set at 5:1. Furthermore, the potential shear failure in the hydrate reservoir is strongly correlated to the in-situ stress state. For the normal fault stress regime, the greater the initial horizontal stress is, the less likely the hydrate reservoir is to undergo shear failure during depressurization production.

Description: Summary Recently, graphics processing units (GPUs) have been demonstrated to provide a significant performance benefit for black-oil reservoir simulation, as well as flash calculations that serve an important role in compositional simulation. A comprehensive approach to compositional simulation based on GPUs has yet to emerge, and the question remains as to whether the benefits observed in black-oil simulation persist with a more complex fluid description. We present a positive answer to this question through the extension of a commercial GPU-basedblack-oil simulator to include a compositional description based on standard cubic equations of state (EOSs). We describe the motivations for the selected nonlinear formulation, including the choice of primary variables and iteration scheme, and support for both fully implicit methods (FIMs) and adaptive implicit methods (AIMs). We then present performance results on an example sector model and simplified synthetic case designed to allow a detailed examination of runtime and memory scaling with respect to the number of hydrocarbon components and model size, as well as the number of processors. We finally show results from two complex asset models (synthetic and real) and examine performance scaling with respect to GPU generation, demonstrating that performance correlates strongly with GPU memory bandwidth. NOTE: This paper is published as part of the 2021 SPE Reservoir Simulation Conference Special Issue.

Description: Summary Selection of a safe mud weight is crucial in drilling operations to reduce costly wellbore-instability problems. Advanced physics models and their analytical solutions for mud-weight-window computation are available but still demanding in terms of central-processing-unit (CPU) time. This paper presents an artificial-intelligence (AI) solution for predicting time-dependent safe mud-weight windows and very refined polar charts in real time. The AI agents are trained and tested on data generated from a time-dependent coupled analytical solution (poroelastic) because numerical solutions are prohibitively slow. Different AI techniques, including linear regression, decision tree, random forest, extra trees, adaptive neuro fuzzy inference system (ANFIS), and neural networks are evaluated to select the most suitable one. The results show that neural networks have the best performances and are capable of predicting time-dependentmud-weight windows and polar charts as accurately as the analytical solution, with 1/1,000 of the computer time needed, making them very applicable to real-time drilling operations. The trained neural networks achieve a mean squared error (MSE) of 0.0352 and a coefficient of determination (R2) of 0.9984 for collapse mud weights, and an MSE of 0.0072 and an R2 of 0.9998 for fracturing mud weights on test data sets. The neural networks are statistically guaranteed to predict mud weights that are within 5% and 10% of the analytical solutions with probability up to 0.986 and 0.997, respectively, for collapse mud weights, and up to 0.9992 and 0.9998, respectively, for fracturing mud weights. Their time performances are significantly faster and less demanding in computing capacity than the analytical solution, consistently showing three-orders-of-magnitude speedups in computational speed tests. The AI solution is integrated into a deployed wellbore-stability analyzer, which is used to demonstrate the AI’s performances and advantages through three case studies.