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A novel experimental and theoretical study on slug dissipation in a horizontal enlarged impacting tee-junction (EIT) is carried out. Both flowing-slug injection and stationary-slug injection into the EIT are studied, and the effects of inlet slug length and liquid-phase fluid properties on the slug dissipation in the EIT are investigated.
A total of 161 experimental data are acquired for air-water and air-oil flow. The flowing-slug data (with a horizontal inlet) show that the slug dissipation length increases with increasing mixture velocity, demonstrating a nonlinear trend with a steeper slope at lower mixture velocities. The effect of superficial gas velocity on the slug dissipation length is more pronounced compared with the effect of superficial liquid velocity. For stationary-slug injection into the EIT (with a 5° upward inclined inlet), the injected slug lengths vary between 40d to 100d (d is the inlet diameter). The data reveal that, when increasing the superficial gas velocity or the inlet slug size, the dissipation length in the EIT branches increases. For this case, the ratio of the slug dissipation length to the inlet slug length is higher for air-water compared with air-oil.
A slug dissipation model is developed using the slug-tracking approach, which is based on the flow mechanisms of liquid shedding at the back of the slug and liquid drainage and penetration of bubble turning at the front of the slug. These phenomena result in different translational velocities at the back and the front of the slug, which result in the dissipation of the slug body. Evaluation of model predictions against the acquired experimental data shows an average absolute relative error of less than 11%.
Temporary-plugging fracturing (TPF) is becoming a promising technique for maximizing the stimulated-reservoir volume in tight reservoirs by injecting diverting agents to plug the preferred perforations and/or hydraulic fractures (HFs). Previous work has developed diverting agents and evaluated their blocking efficiency. However, the mechanism and dominant influence factors of HF growth during TPF remain poorly understood to date, which restricts the application of this technique. To understand the problem and help improve the TPF design, this study simulated the HF-propagation process during TPF in a naturally fractured formation using a previously developed 3D discrete-element-method (DEM) -based complex fracture model. Plugged fracture elements with negligible permeability were incorporated into the model to characterize the blocking intervals of diverting agents within HFs. Parameters, including horizontal differential stress (Δσh), natural-fracture (NF) properties, the number of pluggings, plugging positions, and pumping rate, were investigated to determine their effects on the HF/NF-interaction behavior and the resulting HF geometry. The change in injection pressure before and after plugging under different conditions was also recorded in detail. Modeling results show that the HF/NF-interaction behavior might surprisingly change before and after plugging the preferred HF, ranging from HF crossing of NFs to HF opening of NFs. Notably, Δσh is still the most influential geological parameter that governs the HF-growth behavior during TPF. For a moderate Δσh (=8 MPa), the growth of a single planar HF before plugging can be changed easily into a complex HF network (HFN) through opening of NFs after plugging in the target stimulated region (TSR). In this case, the complexity and covering area of the resulting HFN is closely related to the NF density (positive correlation) and plugging positions. However, for a high Δσh (=12 MPa), opening (usually partially) the NFs after plugging is difficult even in formations with a high density of NFs. In such a case, a large volume of fluid, a high pumping rate, and several repeat pluggings during TPF are necessary. The results of this study help to understand the HF-growth mechanism during TPF and help to optimize the treatment design of TPF and to adjust it in a timely manner.
Liu, Kui (State Key Laboratory of Shale Oil and Gas Enrichment Mechanisms and Effective Development) | Dahi Taleghani, Arash (Sinopec Research Institute of Petroleum Engineering) | Gao, Deli (China University of Petroleum, Beijing)
Summary Casing failure in shale gas wells has seriously impacted production from Weiyuan and Changning fields in Sichuan Province, China. Apparently, interaction of hydraulic fractures with nearby faults causes fault slippage, which in some situations has led to well shearing. Hence, we propose a semianalytical model in this paper to estimate the length of slippage along the fault that is caused by pressurization of a fault intercepted by the hydraulic fracture. These calculations have been performed for different configurations of the fault with respect to the hydraulic fracture and principal stresses. Using the semianalytical model provided in this paper, two fault slippage cases are calculated to assess the casing failure in nearby wells. In one case study, the calculated results of the fault slippage are consistent with the scale of casing deformation in that well and a microseismic magnitude caused by fault slippage is calculated that is larger than the detected events. The presented model will provide a tool for a quick estimation of the magnitude of fault slippage upon intersection with a hydraulic fracture, to avoid potential casing failures and obtain a more reliable spacing selection in the wells intersecting faults. Introduction The shale gas revolution has increased natural-gas supply in the United States and is about to change the world energy map very soon. New technology developments in horizontal drilling and multistage hydraulic fracturing have played critical roles in this revolution. Hydraulic-fracturing treatments mostly take place in multiple stages as thousands of cubic meters of fracturing fluid are injected into the formation in each stage over the course of a few hours. However, a few incidents of fault reactivation as a result of hydraulic fracturing has attracted some attention recently (Wasantha and Konietzky 2016). Before the research on the fault slippage caused by hydraulic fracturing in the shale plays, many earthquakes caused by fluid injection were reported in the literature. The first well-documented earthquake, identified to be caused by fluid injection, occurred in 1960.
Sun, Baojiang (China University of Petroleum, East China) | Fu, Weiqi (China University of Petroleum, East China) | Wang, Zhiyuan (China University of Petroleum, East China) | Xu, Jianchun (China University of Petroleum, East China) | Chen, Litao (China University of Petroleum, East China) | Wang, Jintang (China University of Petroleum, East China) | Zhang, Jianbo (China University of Petroleum, East China)
Methane hydrate slurry in a water-continuous system is a significant production issue during pilot explorations for natural gas and natural gas hydrates in a deepwater environment. This work investigated the morphology and rheology of hydrate slurry with hydrate concentrations from 6 to 11% and shear rates from 20 to 700 s–1. Although hydrate slurry is widely considered a pseudoplastic fluid, in our experiment, hydrate slurry exhibited shear-thinning behavior in low-shear-rate conditions and shear-thickening behavior in high-shearrate conditions. The breakup of agglomerates built up between hydrate particles by shear force induced shear-thinning behavior in low-shear-rate conditions. The collision between monodispersed hydrate particles resulted in shear-thickening behavior in high-shear-rate conditions. The critical shear rate was proposed to describe the transition between the shear-thinning and shear-thickening behaviors of the hydrate slurry, which was a function of the hydrate concentration. Empirical Herschel-Bulkley-type equations were developed to describe the rheology of the hydrate slurry for both conditions.
Summary Loadings acting on a wellbore are more realistically regarded as dynamic rather than static, and the wellbore response under dynamic loading can be different from that under static loading. Under dynamic loading, the inertia term should be considered and the changing rate of loading could induce a change in the mechanical properties of the wellbore, which might compromise wellbore stability and integrity. In this paper, a fully coupled poroelastodynamic model is proposed to study wellbore behavior. This model not only considers fully coupled deformation/diffusion effects, but also includes both solid and fluid inertia terms. The implicit finite-difference method was applied to solve the governing equations, which allows this model to handle all kinds of dynamic loading conditions. The numerical results were validated by comparing them to the analytical solution with a simulated sinusoidal boundary condition. To understand this model better, a sensitivity analysis was performed, and the influence of inertia terms was investigated. After that, the model was applied to analyze wellbore stability under tripping operations. The results show that the inertial effect is insignificant for tripping and a fully coupled, quasistatic model is recommended for wellbore stability under tripping operations. The fully coupled poroelastodynamic model should be used for rapid dynamic loading conditions, such as earthquakes and perforations. Introduction Dynamic loading of a wellbore studies the mechanical behavior of a wellbore under dynamic loading conditions, where a changing rate of loading could lead to changes in mechanical properties and cause wellbore fracturing or instability. Different from static loading, the inertia term should be considered and the mechanical properties of rocks could be changed under dynamic loading conditions.
Surfactant floods can attain high oil recovery if optimal conditions with ultralow interfacial tensions (IFT) are achieved in the reservoir. A recently developed equation-of-state (EoS) phase-behavior net-average-curvature (NAC) model based on the hydrophilic-lipophilic difference (HLD-NAC) has been shown to fit and predict phase-behavior data continuously throughout the Winsor I, II, III, and IV regions. The state-of-the-art for viscosity estimation, however, uses empirical nonpredictive based on of fits to salinity scans, even though other parameters change, such as the phase number and compositions. In this paper, we develop the first-of-its-kind microemulsion viscosity model that gives continuous viscosity estimates in composition space. This model is coupled to our existing HLD-NAC phase-behavior EoS.
The results show that experimentally measured viscosities in all Winsor regions (two- and three-phase) are a function of phase composition, temperature, pressure, salinity, and the equivalent alkane carbon number (EACN). More specifically, microemulsion viscosities associated with the three-phase invariant point have an M shape as formulation variables change, such as from a salinity scan. The location and magnitude of viscosity peaks in the M are predicted from two percolation thresholds after tuning to viscosity data. These percolation thresholds as well as other model parameters change linearly with EACN and brine salinity. We also show that the minimum viscosity in the M shape correlates linearly with EACN or the viscosity ratio. Other key parameters in the model are also shown to linearly correlate with the EACN and brine salinity. On the basis of these correlations, two- and three-phase microemulsion viscosities are determined in five-component space (surfactant, two brine components, and two oil components) independent of flash calculations. Phase compositions from the EoS flash calculations are entered into the viscosity model. Fits to experimental data are excellent, as well as viscosity predictions for salinity scans not used in the fitting process.
Most wells in carbonate reservoirs are stimulated. Because of their low cost and simpler operations, acid-stimulation methods are usually preferred if they are sufficient. Matrix acidizing can effectively stimulate carbonate reservoirs, often resulting in skin factors on the order of –3 to –4. In low confining stress and hard rocks, acid fracturing can yield better results than matrix acidizing. However, acid fracturing is less effective in high permeability, high confining stress, or soft rocks. There is a combination of parameters, among them permeability, confining stress, and rock geomechanical properties, that can be used as criteria to decide whether matrix acidizing or acid fracturing is the best acid-stimulation technique for a given scenario.
This study compares the productivity of matrix-acidized and acid-fractured wells in carbonate reservoirs. The criterion used to decide the preferred method is the largest productivity obtained using the same volume of acid for both operations. The productivity of the acid-fractured wells is estimated using a fully coupled acid-fracturing simulator, which integrates the geomechanics (fracture propagation), pad and acid transport, heat transfer, temperature effect on reaction rate, effect of wormhole propagation on acid leakoff, and finally calculates the well productivity by simulating the flow in the reservoir toward the acid fracture. Using this simulator, the acid-fracturing operation is optimized, resulting in the operational conditions (injection rate, type of fluid, amount of pad, and so forth) that lead to the best possible acid fracture that can be created with a given amount of acid. The productivity of the matrix-acidized wells is estimated using the most recent wormhole-propagation models scaled up to field conditions.
Results are presented for different types of rock and reservoir scenarios, such as shallow and deep reservoirs, soft and hard limestones, chalks, and dolomites. Most of the presented results considered vertical wells. A theoretical extension to horizontal wells is also presented using analytical considerations. For each type of reservoir rock and confining stress, there is a cutoff permeability less than which acid fracturing results in a more productive well; at higher than this cutoff permeability, matrix acidizing should be preferred. This result agrees with the general industry practice, and the estimated productivity agrees with the results obtained in the field. However, the value of the cutoff permeability changes for each case, and simple equations for calculating it are presented. For example, for harder rocks or shallower reservoirs, acid fracturing is more efficient up to higher permeabilities than in softer rocks or at deeper depths.
This method provides an engineered criterion to decide the best acid-stimulation method for a given carbonate reservoir. The decision criterion is presented for several different scenarios. A simplified concise analytical decision criterion is also presented: a single dimensionless number that incorporates all pertinent reservoir properties and determines which stimulation method yields the most productive well, without needing any simulations.
Li, Xin (Peking University) | Li, Xiang (Qingdao Dadi Institute of New Energy Technologies) | Zhang, Dongxiao (Southern University of Science and Technology) | Yu, Rongze (Research Institute of Petroleum Exploration and Development)
Summary In the development of fractured reservoirs, geomechanics is crucial because of the stress sensitivity of fractures. However, the complexities of both fracture geometry and fracture mechanics make it challenging to consider geomechanical effects thoroughly and efficiently in reservoir simulations. In this work, we present a coupled geomechanics and multiphase-multicomponent flow model for fractured reservoir simulations. It models the solid deformation using a poroelastic equation, and the solid deformation effects are incorporated into the flow model rigorously. Because of the separation of the geomechanics part and the flow part, the model is not difficult to implement based on an existing reservoir simulator. We validated the accuracy and stability of this model through several benchmark cases and highlighted the practicability with two large-scale cases. The case studies demonstrate that this model is capable of considering the key effects of geomechanics in fractured-reservoir simulation, including matrix compaction, fracture normal deformation, and shear dilation, as well as hydrocarbon phase behavior. The flexibility, efficiency, and comprehensiveness of this model enable a more realistic geocoupled reservoir simulation. Introduction Fractured reservoirs, including naturally fractured reservoirs and artificially fractured reservoirs, contribute 60% of the world's oil and gas storage and have attracted intense attention in the past two decades. During the production of such reservoirs, stress perturbation induces fracture deformation, and fracture permeability changes significantly, because of its high stress sensitivity. As a result, production is greatly affected. To simulate fractured reservoirs accurately, reservoir models should couple geomechanics, and the geocoupled model should consider fracture effects.
Ferreira, Carla Janaina (Durham University and University of Campinas) | Vernon, Ian (Durham University) | Caiado, Camila (Durham University) | Formentin, Helena Nandi (Durham University and University of Campinas) | Avansi, Guilherme Daniel (University of Campinas) | Goldstein, Michael (Durham University) | Schiozer, Denis José (University of Campinas)
When performing classic uncertainty reduction according to dynamic data, a large number of reservoir simulations need to be evaluated at high computational cost. As an alternative, we construct Bayesian emulators that mimic the dominant behavior of the reservoir simulator, and which are several orders of magnitude faster to evaluate. We combine these emulators within an iterative procedure that involves substantial but appropriate dimensional reduction of the output space (which represents the reservoir physical behavior, such as production data), enabling a more effective and efficient uncertainty reduction on the input space (representing uncertain reservoir parameters) than traditional methods, and with a more comprehensive understanding of the associated uncertainties. This study uses the emulation-based Bayesian history-matching (BHM) uncertainty analysis for the uncertainty reduction of complex models, which is designed to address problems with a high number of both input and output parameters. We detail how to efficiently choose sets of outputs that are suitable for emulation and that are highly informative to reduce the input-parameter space and investigate different classes of outputs and objective functions. We use output emulators and implausibility analysis iteratively to perform uncertainty reduction in the input-parameter space, and we discuss the strengths and weaknesses of certain popular classes of objective functions in this context. We demonstrate our approach through an application to a benchmark synthetic model (built using public data from a Brazilian offshore field) in an early stage of development using 4 years of historical data and four producers. This study investigates traditional simulation outputs (e.g., production data) and also novel classes of outputs, such as misfit indices and summaries of outputs. We show that despite there being a large number (2,136) of possible outputs, only very few (16) were sufficient to represent the available information; these informative outputs were used using fast and efficient emulators at each iteration (or wave) of the history match to perform the uncertainty-reduction procedure successfully. Using this small set of outputs, we were able to substantially reduce the input space by removing 99.8% of the original volume. We found that a small set of physically meaningful individual production outputs were the most informative at early waves, which once emulated, resulted in the highest uncertainty reduction in the input-parameter space, while more complex but popular objective functions that combine several outputs were only modestly useful at later waves. The latter point is because objective functions such as misfit indices have complex surfaces that can lead to low-quality emulators and hence result in noninformative outputs. We present an iterative emulator-based Bayesian uncertainty-reduction process in which all possible input-parameter configurations that lead to statistically acceptable matches between the simulated and observed data are identified. This methodology presents four central characteristics: incorporation of a powerful dimension reduction on the output space, resulting in significantly increased efficiency; effective reduction of the input space; computational efficiency, and provision of a better understanding of the complex geometry of the input and output spaces.
Foam increases sweep efficiency during gas injection in enhanced oil recovery processes. Surfactant alternating gas (SAG) is the preferred method to inject foam for both operational and injectivity reasons. Dynamic SAG corefloods are unreliable for direct scaleup to the field because of core-scale artifacts. In this study, we report fit and scaleup local-equilibrium (LE) data at very-low injected-liquid fractions in a Bentheimer core for different surfactant concentrations and total superficial velocities.
We fit LE data to an implicit-texture foam model for scaleup to a dynamic foam process on the field scale using fractional-flow theory. We apply different parameter-fitting methods (least-squares fit to entire foam-quality scan and the method of Rossen and Boeije 2015) and compare their fits to data and predictions for scaleup. We also test the implications of complete foam collapse at irreducible water saturation for injectivity.
Each set of data predicts a shock front with sufficient mobility control at the leading edge of the foam bank. Mobility control improves with increasing surfactant concentration. In every case, scaleup injectivity is much better than with coinjection of gas and liquid. The results also illustrate how the foam model without the constraint of foam collapse at irreducible water saturation (Namdar Zanganeh et al. 2014) can greatly underestimate injectivity for strong foams.
For the first time, we examine how the method of fitting the parameters to coreflood data affects the resulting scaleup to field behavior. The method of Rossen and Boeije (2015) does not give a unique parameter fit, but the predicted mobility at the foam front is roughly the same in all cases. However, predicted injectivity does vary somewhat among the parameter fits. Gas injection in a SAG process depends especially on behavior at low injected-water fraction and whether foam collapses at the irreducible water saturation, which may not be apparent from a conventional scan of foam mobility as a function of gas fraction in the injected foam. In two of the five cases examined, this method of fitting the whole scan gives a poor fit for the shock in gas injection in SAG. We also test the sensitivity of the scaleup to the relative permeability krw(Sw) function assumed in the fit to data.
There are many issues involved in scaleup of laboratory data to field performance: reservoir heterogeneity, gravity, interactions between foam and oil, and so on. This study addresses the best way to fit model parameters without oil for a given permeability, an essential first step in scaleup before considering these additional complications.