Numerical Simulation Study of Proppant Transport in Cross Fractures

Hydraulic fracturing technology is an important means to stimulate unconventional reservoirs, and the placement morphology of proppant in cross fractures is a key factor affecting the effect of hydraulic fracturing. It is very important to study the proppant transport law in cross fractures. In order to study the proppant transportation law in cross fractures, based on the CFD-DEM method, a proppant transport model in cross fractures was established. From the two aspects of the flow field in the fractures and the morphology of the proppant dune, the influence of the natural fracture approach angle, the fracturing fluid viscosity and injection rate on the proppant transport is studied. Based on the principle of hydropower similarity, the conductivity of proppant dune under different conditions is quantitatively studied. The results show that the natural fracture approach angle affects the distribution of proppant and fracturing fluid in natural fractures, and further affects the proppant placement morphology in hydraulic fractures and natural fractures. When the fracturing fluid viscosity is low and the displacement is small, the proppant forms a "high and narrow" dune at the entrance of the fracture. With the increase of the fracturing fluid viscosity and injection rate, the proppant settles to form a "short and wide" placement morphology. Compared with the natural fracture approach angle, the fracturing fluid viscosity and injection rate have a more significant impact on the conductivity of proppant dune. This paper investigated the proppant transportation in cross fractures, and quantitatively analyzes the conductivity of proppant dunes with different placement morphology. The results of this study can provide theoretical guidance for the design of hydraulic fracturing.

Experimental Study of Proppant Bridging in a Model of a Hydraulic Fracture

Summary In this article, we investigate formation of the local clogging (bridging) of proppant in a channel with gradually narrowing walls. The experimental facility allows us to simulate the process of the proppant transport in a hydraulic fracture by reproduction of the characteristic channel width, velocity of slurry, rheology of fracturing fluids, and typical concentrations of proppant. The goal of the study is to give qualitative description of the dynamics of the congestion of the proppant up to the complete blockage of the flow. In contrast to common practice of imposing bridging criteria by postulating certain threshold value of the width to proppant size ratio, we demonstrate that the bridging process involves several stages: clogging of two to three particles, growth of stable “islands,” connection of the islands by arches, and, finally, the total sandout of the cell by the bridged proppant. The observations of the paper gives better understanding of the bridging process giving the directions for more precise numerical simulations.

High Performance Friction Reducer for Slickwater Fracturing Applications: Laboratory Study and Field Implementation

Proppant placement in a tight formation is extremely challenging. Therefore, using a high viscous friction reducer (HVFR) as a fracturing fluid for stimulation treatment in tight gas reservoirs is increasing within the industry because it can transport proppant, help reduce pipe friction generated during hydraulic-fracturing treatments, and efficiently clean up similar to the lower viscosity friction reducers (FRs). In this paper the implementation of the robust HVFR that is building higher viscosity at low concentrations, which minimizes energy loss and promotes turbulent flow within the pipe during the pumping of low viscosity, is discussed in detail. Performance evaluation of the new HVFR was conducted in the laboratory and compared to the lower viscosity FR. The study consisted of viscosity measurements at 70 and 180°F, compatibility with other additives, and proppant transport capabilities. Additionally, the viscosity generated from both FRs was compared using two water sources: water well A and treated sewage water. Viscosity measurements were performed across a wide range of FR and HVFR concentrations and under varying shear rates using a digital viscometer. To validate drag reduction capabilities for this HVFR in the field, the same groundwater with low salinity and low total dissolved solids (TDS) content were used for comparison purposes. The test plan for this new HVFR was for a well to be drilled to a total depth of 17,801 ft MD (10,693 ft TVD) with a 6,016-ft lateral section. Another part of the plan was to complete 41 stages—the first stage with the toe initiator, and subsequent stages using ball drops until Stage 8, were completed using the current FR. For Stage 8, the drag reduction from the new HVFR was evaluated against the current FR only during the pad stage. Then, FR or HVFR concentrations were used, with a gradual reduction from 2 to 1 gpt without compromising proppant placement from stages 9 to 37, alternating current FR and the new HVFR every four stages. From Stage 38 to 41, the same approach was used but with treated sewage water and alternating every other stage using current FR or HVFR at 1gpt. The implementation of the new HVFR showed better friction reduction when using the same concentration of the current FR. Also, achieving better average treating pressures with lower concentration. Based on that it is a cost-effective solution and the performance is better, this lead to reduce the HVFR volume to be pumped per stage compared to the current FR. Applications/Significance/Novelty For this study, drag reduction capabilities for this new HVFR were validated in the field at higher pumping rate conditions, potentially optimizing (reducing) the polymer concentration during a freshwater application. It was shown that lower concentrations of this HVFR provided higher viscosity, which helps improve proppant transport and operation placement.

Evaluating essential features of proppant transport at engineering scales combining field measurements with machine learning algorithms

The characterization of the proppant transport at a field-engineering scale is still challenging due to the lack of direct subsurface measurements. Features that control the proppant transport may link the experimental and numerical observations to the practical operations at a field scale. To improve the numerical and laboratory simulations, we propose a machine-learning-based workflow to evaluate the essential features of proppant transport and their corresponding calculations. The proppant flow in fractures is estimated by applying the Gated recurrent unit (GRU) and Support-vector machine (SVM) algorithms to the measurements obtained from shale gas fracturing operations. Over 430,000 groups of fracturing data are collected and pre-processed by the proppant transport models to calculate key features, including settlement, stratified flow and inception of settled particles. The features are then fed into machine learning algorithms for pressure prediction. The root mean squared error (RMSE) is used as the criterion for ranking selected features via the control variate method. Our result shows that the stratified-flow feature (fracture-level) possesses better interpretations for the proppant transport, in which the Bi-power model helps to produce the best predictions. The settlement and inception features (particle-level) perform better in cases that the pressure fluctuates significantly, indicating that more complex fractures may have been generated. Moreover, our analyses on the remaining errors in the pressure-ascending cases suggest that (1) an introduction of the alternate-injection process, and (2) the improved calculation of proppant transport in complex fracture networks and highly-filled fractures will be beneficial to both experimental observations and field applications.

Numerical Simulation of Proppant Transport in Hydraulically Fractured Reservoirs

An existing equation-of-state compositional simulator is extended to include proppant transport. The simulator determines the final location of the proppant after fracture closure, which allows the computation of the permeability along the hydraulic fracture. The simulation then continues until the end of the production. During hydraulic fracturing, proppant is injected in the reservoir along with water and additives like polymers. Hydraulic fracture gets created due to change in stress caused by the high injection pressure. Once the fracture opens, the bulk slurry moves along the hydraulic fracture. Proppant moves at a different speed than the bulk slurry and sinks down by gravity. While the proppant flows along the fracture, some of the slurry leaks off into the matrix. As the fracture closes after injection stops, the proppant becomes immobile. The immobilized proppant prevents the fracture from closing and thus keeps the permeability of the fracture high. All the above phenomena are modelled effectively in this new implementation. Coupled geomechanics simulation is used to model opening and closure of the fracture following geomechanics criteria. Proppant retardation, gravitational settling and fluid leak-off are modeled with the appropriate equations. The propped fracture permeability is a function of the concentration of immobilized proppant. The developed proppant simulation feature is computationally stable and efficient. The time step size during the settling adapts to the settling velocity of the proppants. It is found that the final location of the proppants is highly dependent on its volumetric concentration and slurry viscosity due to retardation and settling effects. As the location and the concentration of the proppants determine the final fracture permeability, the additional feature is expected to correctly identify the stimulated region. In this paper, the theory and the model formulation are presented along with a few key examples. The simulation can be used to design and optimize the amount of proppant and additives, injection timing, pressure, and well parameters required for successful hydraulic fracturing.