A Semi-Analytical Geomechanical Approach for Forecasting Production Performance in Multifractured Composite Systems

Stress-dependence of reservoir matrix and fractures can strongly affect the performance of multifractured horizontal wells (MFHWs) completed in unconventional hydrocarbon reservoirs. In order to model fluid flow in unconventional reservoirs exhibiting this stress-dependence, most traditional reservoir flow simulators, and many simulators described in published work, use conventional reservoir fluid flow model formulations. These formulations typically neglect the influence of the rate of change of volumetric strain of the reservoir matrix and fractures, even though reservoir stress and pressure change significantly during the course of production. As a result, the effect of matrix and fracture deformation on production is neglected, which can lead to errors in predicting production performance in most stress-sensitive reservoirs. To address this problem, some studies have proposed the use of porosity and transmissibility multipliers to model stress-sensitive reservoirs. However, in order to apply this approach, multipliers must be estimated from laboratory experiments, or used as a history-match parameter, possibly resulting in large errors in well performance predictions. Alternatively, fully-coupled, fully numerical geomechanical simulation can be performed, but these methods are computationally costly, and models are difficult to setup. This paper presents a new fully-coupled, two-way analytical modeling approach that can be used to simulate fluid flow in stress-sensitive unconventional reservoirs produced through MFHWs. The model couples poroelastic geomechanics theory with fluid flow formulations. The two-way coupled fluid flow-geomechanical analytical model is applied simultaneously to both the matrix and fracture regions. In the proposed algorithm, a porosity-compressibility coupling parameter for the two physical models is setup to update the stress- and pressure-dependent fracture/matrix properties iteratively, which are later used as input data for the fracture-matrix reservoir fluid flow model at each iteration step. The analytical approach developed for the fully-coupled, two-way analytical model, using the enhanced fracture region conceptual model, is validated by comparing the results with numerical simulation. Predictions using the fully-coupled enhanced fracture region model are then compared with the same enhanced fracture region model but with the conventional pressure-dependent modeling approach implemented. A sensitivity study performed by comparing the new fully-coupled model predictions with and without geomechanics effects accounted for reveals that, without geomechanics effects, production performance in stress-sensitive reservoirs might be overestimated. The study also demonstrates that use of the conventional stress-dependent modeling approach may cause production performance to be underestimated. Therefore, the proposed fully-coupled, two-way analytical model can be useful for practical engineering purposes.

Modeling the airflow field of vortex spinning

Vortex spinning technology adopts a high-speed swirling airflow to rotate the fibers with open-ends to form yarn with real twists. The airflow behavior within the nozzle has a great effect on the yarn-formation process. In this study, a three-dimensional calculation nozzle model and corresponding three-dimensional airflow region model were established to enable the numerical calculation; airflow behavior—pressure, velocity, and the turbulent airflow field, and the streamline of airflow—was investigated in the presence of fiber bundles within the vortex spinning nozzle. Hybrid hexahedral/tetrahedral control volumes were utilized to mesh the grids in the calculation region. To consider airflow diffusion and convection in the nozzle, the Realizable k- ε turbulence model with wall function was adopted to conduct the calculation. Dynamic and static pressure values were obtained by numerical analysis to predict the action of the inner surface of nozzle and the wall resistance on the high-speed swirling airflow. The numerical simulation of dynamic airflow behavior can generate great insight into the details of airflow behavior and its distribution characteristics, and is helpful for understanding the spinning mechanism and promoting optimization of the spinning process.

Constraints on near-source saturation models for avoiding over-saturation of response spectral ordinates in RVT-based stochastic ground-motion simulations

Inversions of empirical data and ground-motion models to find Fourier spectral parameters can result in parameter combinations that produce over-saturation of short-period response spectral ordinates. While some evidence for over-saturation in empirical data exists, most ground-motion modellers do not permit this scaling within their models. Host-to-target adjustments that are made to published ground-motion models for use in site-specific seismic hazard analyses frequently require the identification of an equivalent set of Fourier spectral parameters. In this context, when inverting response spectral models that do not exhibit over-saturation effects, it is desirable to impose constraints upon the Fourier parameters to match the scaling of the host-region model. The key parameters that determine whether over-saturation arises are the geometric spreading rate (γ) and the exponential rate within near-source saturation models (hβ). The article presents the derivation of simple nonlinear constraints that can be imposed to prevent over-saturation when undertaking Fourier spectral inversions.

Theft Prediction Model Based on Spatial Clustering to Reflect Spatial Characteristics of Adjacent Lands

Previous studies have shown that when a crime occurs, the risk of crime in adjacent areas increases. To reflect this, previous grid-based crime prediction studies combined all the cells surrounding the event location to be predicted for use in model training. However, the actual land is continuous rather than a set of independent cells as in a geographic information system. Because the patterns that occur according to the detailed method of crime vary, it is necessary to reflect the spatial characteristics of the adjacent land in crime prediction. In this study, cells with similar spatial characteristics were classified using the Max-p region model (a spatial clustering technique), and the performance was compared to the existing method using random forest (a tree-based machine learning model). According to the results, the F1 score of the model using spatial clustering increased by approximately 2%. Accordingly, there are differences in the physical environmental factors influenced by the detailed method of crime. The findings reveal that crime involving the same offender is likely to occur around the area of the original crime, indicating that a repeated crime is likely in areas with similar spatial features to the area where the crime occurred.

Relationship between prediction skill of surface winds in average of weeks 1 to 4 and interannual variability over the Western Pacific and Indian Ocean

This study examines the possible relationship between predictions of weekly and biweekly averages of 10m winds at 3 weeks lead-time and interannual variability over Western Pacific and Indian Ocean (WP-IO) using Climate Forecast System version 2 (CFSv2) reforecasts for period 1979-2008. There is large temporal correlation between forecasts and reanalyses for zonal, meridional and total wind magnitudes at 10m over most of WP-IO for average of weeks 1 and 2 (W1 and W2) in reforecasts initialized in January (JIR) and May (MIR). The model has some correlations that exceed 95% confidence in some portions of WP-IO in week 3 (W3) but no skill in week 4 (W4) over most of the region. Model depicts prediction skill in 14-day average of weeks 3-4 (W3-4) over portions of WP-IO, similar to level of skill in W3. The amplitude of interannual variability (IAV) for 10m-winds in W1 of JIR and MIR is close to that in reanalyses. As lead-time increases, amplitude of IAV of 10m-winds gradually decreases over WP-IO in reforecasts; in contrast to behavior in reanalyses. The amplitude of IAV of predicted 10m-winds in W3-4 over WP-IO is equivalent to that in W3 and W4 in reforecasts. In contrast, the amplitude of IAV in W3-4 in January and May of reanalysis is much smaller than IAV of W3 and W4. Therefore, one of the possible causes for prediction skill in W3-4 over sub-regions of WP-IO is due to reduction of IAV bias in W3-4 in comparison to IAV bias in W3 and W4.

Diffusion and reaction in pore hierarchies by the two-region model

The two-region (“Kärger”) model of diffusion in complex pore spaces is exploited for quantitating mass transfer in hierarchically organized nanoporous materials, consisting of a continuous microporous bulk phase permeated by a network of transport pores. With the implications that the diffusivity in the transport pores significantly exceeds the diffusivity in the micropores and that the relative population of the transport pores is far below that of the micropores, overall transport depends on only three independent parameters. Depending on their interrelation, enhancement of the overall mass transfer is found to be ensured by two fundamentally different mechanisms. They are referred to as the limiting cases of fast and slow exchange, with the respective time constants of molecular uptake being controlled by different parameters. Complemented with reaction terms, the two-region model may equally successfully be applied to the quantitation of the combined effect of diffusion and reaction in terms of the effectiveness factor. Generalization of the classical Thiele concept is shown to provide an excellent estimate of the effectiveness factor of a chemical reaction in hierarchically porous materials, solely based on the intrinsic reaction rate and the time constant of molecular uptake relevant to the given conditions.

Effect of Temperature on Formaldehyde Diffusion in Cellulose Amorphous Region: A Simulation Study

A formaldehyde-cellulose amorphous region model at the micro-level was established using the molecular dynamics software Materials Studio to simulate the change of cellulose and formaldehyde molecules in an external temperature field. The diffusion coefficients of formaldehyde molecules increased as the temperature increased. Moreover, the total number of hydrogen bonds decreased, and the interaction energy in the formaldehyde-cellulose model was reduced, which confirmed this conclusion and indicated that temperature increase could enhance the diffusion of formaldehyde in cellulose. The mechanical parameters of cellulose were analyzed in terms of Young’s modulus, shear modulus, bulk modulus, Poisson’s ratio, and the ratio of bulk modulus to shear modulus (K/G), which were affected by the temperature. The elastic modulus (E, G, and K) of cellulose decreased as the temperature increased, while the Poisson’s ratio V and K/G values increased. The results of the research explain how elevated temperature can promote the release of formaldehyde in furniture from a microscopic perspective, which supports each other with the results of previous experimental data and practical applications in production.

Analysis of Production Data from Communicating Multifractured Horizontal Wells Using the Dynamic Drainage Area Concept

Summary Reduction of fracture/well spacing and increases in hydraulic fracture stimulation treatment size are popular strategies for improving hydrocarbon recovery from multifractured horizontal wells (MFHWs). However, these strategies can also increase the chance of fracture interference, which can not only negatively impact the overall production but also introduce complexities for production data analysis. A semianalytical model is therefore developed to analyze production data from two communicating MFHWs and applied to a field case. The new semianalytical model uses the dynamic drainage area (DDA) concept and assumes three porosity regions. The three-region model is comprised of a primary hydraulic fracture (PHF), an enhanced fractured region (EFR) adjacent to the PHF, and a nonstimulated region (NSR). Assuming a well pair primarily communicates through PHFs, the equations for two communicating wells are coupled and solved simultaneously to model the fluid transfer between the wells. This method is used within a history-matching framework to estimate the communication between the wells by matching the production data. The semianalytical model is first verified against a more rigorous, fully numerical simulation model for a range of fracture/reservoir properties. These comparisons demonstrate that there is excellent agreement between the fully numerical simulation model results and the new semianalytical model. The semianalytical model is then employed to history-match production data from six MFHWs (drilled from two adjacent well pads) exhibiting different degrees of communication. For the purpose of history matching the data, only strong communication between pairs of wells (intrapair communication) is considered in the three-region model, and the results show good agreement with the field data. A flexible, yet simple, semianalytical model is developed for the first time that can accurately model the communication between multiple well pairs. This approach can be used by reservoir engineers to analyze the production data from communicating MFHWs.