Many stimulated shale-gas wells experience surprisingly low fracturing-fluid recoveries. Fracture closure, gravity segregation, proppant distribution, and shut-in (soaking) time have been widely postulated to be the contributing factors. This study examines the effects of these factors on fracturing-fluid distribution and subsequent well performance using flow and geomechanical simulations. In the end, two real-field examples are used to validate the findings in this study.
Geomechanical simulation is used to capture the complex post-closure fracture geometry caused by nonuniform proppant distribution. The geometry is then passed into a series of 3D numerical flow models that are constructed using petrophysical parameters, fluid properties, and operational constraints representative of the Horn River shale-gas reservoir. Within the flow simulation, the hydraulic fracture is represented explicitly in the computational domain by means of local-grid refinement, and the physical process of fracture closure during shut-in and production periods is modeled by adjusting the fracture volume and fracture conductivity dynamically. Non-Darcy behavior caused by high gas velocity in the fracture and matrix desorption are considered. The results of the geomechanical simulation confirm the formation of a residual opening above the proppant pack in a partially propped fracture. The residual opening offers a highly conductive flow path for the gas, which is much more mobile than the water-based fracturing fluid, and this difference in mobility further aggravates gravity segregation. Gravity segregation might lead to water accumulating near the bottom of a vertical planar fracture, but reduced fracture conductivity could limit the segregation and promote a more uniform fluid distribution. Water uptake into the matrix is influenced by forced and spontaneous imbibition caused by the large pressure differential across the matrix/ fracture interface and matrix capillarity. Additional water is displaced into the matrix as pressure depletes and the fracture closes. Fracturing-fluid-penetration depth increases with shut-in time, resulting in an enhancement in the initial gas rate, but lower late-time production is also observed.
Analysis of the residual opening of a partially propped fracture and its role in fracturing-fluid distribution in three dimensions is novel. Field examples suggest that considering the various physical mechanisms investigated in this study could improve the accuracy of the numerical model for history matching and the reliability of the ensuing production forecasting. The findings in this study might provide a better understanding of fracturing-fluid distribution, which is useful for optimizing production strategies and operations concerning hydraulically fractured shale-gas reservoirs.
The majority of the models in the literature for the steam-assisted-gravity-drainage (SAGD) process solve the problem of conductive heat transfer ahead of a moving hot interface using a quasisteady-state assumption and extend the solution to the base of the steam chamber where the interface is not moving. This approach, as discussed by Butler (1985) and Reis (1992), results in inaccurate or sometimes infeasible estimations of the oil-production rate, steam/oil ratio (SOR), and steam-chamber shape. In this work, a new approach for the analytical treatment of SAGD is proposed in which the problem of heat transfer is directly solved for a stationary source of heat at the base of the steam chamber, where the oil production occurs. The distribution of heat along the interface is then estimated depending on the geometry of the steam chamber.
This methodology is more representative of the heat-transfer characteristics of SAGD and resolves the challenges of those earlier models. In addition, it allows for the extension of the formulations to the early stages of the process when the side interfaces of the chamber are almost stationary, without loss of the solution continuity. The model requires the overall shape of the steam chamber as an input. It then estimates the movement of chamber interfaces using the movement of the uppermost interface point and by satisfying the global material-balance requirements. Oil-production rate and steam demand are estimated by Darcy’s law and energy-balance calculations, respectively. The result is a model that is applicable to the entire lifetime of a typical SAGD project and provides more-representative estimations of in-situ heat distribution, bitumen-production rate, and SOR.
With the improved knowledge obtained on the fundamentals of heat transfer in SAGD, the reason for the discrepancies between the various earlier models will be clarified. Results of the analytical models developed in this work show reasonable agreement with fine-scale numerical simulation, which indicates that the primary physics are properly captured. In the final section of the paper, the application of the developed models to two field case studies will be demonstrated.
A hybrid-hydraulic-fracture (HHF) model composed of (1) complex discrete fracture networks (DFNs) and (2) planar fractures is proposed for modeling the stimulated reservoir volume (SRV). Modeling the SRV is complex and requires a synergetic approach between geophysics, petrophysics, and reservoir engineering. The objective of this paper is to characterize and evaluate the SRV in nine horizontal multilaterals covering the Muskwa, Otter Park, and Evie Formations in the Horn River Shale in Canada, with a view to match their production histories and to evaluate the effectiveness and potential problems of the multistage hydraulic-fracturing jobs performed in the nine laterals.
To accomplish this goal, the HHF model is run in a numerical-simulation model to evaluate the SRV performance in planar and complex fracture networks using good-quality microseismicity data collected during 75 stages of hydraulic fracturing (out of 145 stages performed in nine laterals). The fracture-network geometry for each hydraulic-fracture (HF) stage is developed on the basis of microseismicity observations and the limits obtained in the fracture-propagation modeling. Post-fracturing production is appraised with rate-transient analysis (RTA) for determining effective permeability under flowing conditions. Results are compared with the HHF simulation and the hydraulic-fracturing design.
The HHF modeling of the SRV leads to a good match of the post-fracturing production history. The HHF simulation indicates interference between stages. The vertical connectivity in the reservoir is larger than the horizontal connectivity. This is interpreted to be the result of the large height achieved by HFs, and the absence of barriers between the formations.
It is concluded that the HHF model is a valuable tool for evaluating hydraulic-fracturing jobs and the SRV in shales of the Horn River Basin in Canada. Because of the generality of the Horn River application, the same approach might have application in other shale gas reservoirs around the world.
The objective of this paper is to couple wellbore and surface-production-facilities models with reservoir simulation for a shale reservoir that contains dry gas, condensate, and oil in separate geologic containers within the same structure. The goal of this integration is to improve liquid recoveries by dry-gas injection and gas recycling.
Methods previously published investigate possible means of improving recovery from shales and have concentrated on laboratory work and the reservoir itself, but have ignored the wellbore and surface-production facilities. The coupling of these facilities in the simulation work is critical, particularly in cases involving condensate and oil reservoirs, gas injection, and recycling operations. This is so, because a change in pressure in the reservoir is reflected almost immediately in a change in pressure in the wellbore and in the surface installations.
The development presented in this paper considers multistage hydraulically fractured horizontal wells. Dry gas is injected into zones that contain condensate and oil. Gas stripped from the condensate production is reinjected in the condensate zone in a recycling operation. The study focuses on the Eagle Ford Shale, which has separate containers for each fluid within the same structure.
The study leads to the conclusion that, for the studied system, liquid recoveries can be maximized with continuous and huff ’n’ puff gas-injection schemes. In general, huff ’n’ puff injection provides better results in terms of production and economics. Molecular diffusion is found to play a crucial role in continuous gas-injection operations. Conversely, the effect of this phenomenon is negligible in huff ’n’ puff gas injection. This research demonstrates that proper design of wellbore and surface installations, including, for example, downhole pumps and compressors, is important because it plays a critical role in the performance of production and injection operations and in maximizing recovery of liquids from shale reservoirs.
The novelty of the methodology developed in this paper is the coupling of models that handle surface facilities; wellbores; numerical simulation including oil, condensate, and dry-gas reservoirs; gas injection; and gas/condensate-recycling operations. Essentially, the shale containers, wellbore, and surface facilities are continuously “talking” to each other. To the best of our knowledge, this integration for shales has not been published previously in the literature.
Coinjection of solvent with steam in steam-assisted gravity drainage (SAGD) has shown promising results for enhancing oil rates as well as reducing energy and water consumption. Modeling and optimizing hybrid-steam/solvent-recovery processes by use of commercial numerical simulators can be very time-consuming. Semianalytical mathematical models may be used to estimate production rates and thermal efficiency in much less time.
In this study, an unsteady-state semianalytical model was developed to predict the oil-flow rate in the steam/solvent assisted-recovery process. The model assumes a curved interface with transient temperature and solvent distribution in the mobile zone. It also accounts for transverse dispersion and concentration dependent molecular diffusion for solvent distribution. The oil-flow rate and interface profile are predicted at each time in an iterative fashion. The model is validated against the CMG-STARS thermal simulator as well as experimental results for hexane-aided SAGD physical-model tests. The semianalytical model was able to predict oil-production rates by use of different solvents coinjected with steam, in agreement with reported experimental data.
The proposed model accounts for the complex interaction of heat and solvent solubility and diffusion as they affect mobilization and production of viscous oil. This model may be used to estimate the optimal operation parameters for the process over a range of different reservoir qualities and pressures, in a very time-efficient manner. The final outcome may lead to an efficient design of a steam/solvent-recovery process that uses less water and reduces the amount of energy and gas emissions per barrel of oil produced.
Advancements in horizontal-well drilling and multistage hydraulic fracturing have enabled economically viable gas production from tight formations. Reservoir-simulation models play an important role in the production forecasting and field-development planning. To enhance their predictive capabilities and to capture the uncertainties in model parameters, one should calibrate stochastic reservoir models to both geologic and flow observations.
In this paper, a novel approach to characterization and history matching of hydrocarbon production from a hydraulic-fractured shale is presented. This new methodology includes generating multiple discrete-fracture-network (DFN) models, upscaling the models for numerical multiphase-flow simulation, and updating the DFN-model parameters with dynamic-flow responses. First, measurements from hydraulic-fracture treatment, petrophysical interpretation, and in-situ stress data are used to estimate the initial probability distribution of hydraulic-fracture and induced-microfracture parameters, and multiple initial DFN models are generated. Next, the DFN models are upscaled into an equivalent continuum dual-porosity model with analytical techniques. The upscaled models are subjected to the flow simulation, and their production performances are compared with the actual responses. Finally, an assisted-history-matching algorithm is implemented to assess the uncertainties of the DFN-model parameters. Hydraulic-fracture parameters including half-length and transmissivity are updated, and the length, transmissivity, intensity, and spatial distribution of the induced fractures are also estimated.
The proposed methodology is applied to facilitate characterization of fracture parameters of a multifractured shale-gas well in the Horn River basin. Fracture parameters and stimulated reservoir volume (SRV) derived from the updated DFN models are in agreement with estimates from microseismic interpretation and rate-transient analysis. The key advantage of this integrated assisted-history-matching approach is that uncertainties in fracture parameters are represented by the multiple equally probable DFN models and their upscaled flow-simulation models, which honor the hard data and match the dynamic production history. This work highlights the significance of uncertainties in SRV and hydraulic-fracture parameters. It also provides insight into the value of microseismic data when integrated into a rigorous production-history-matching work flow.
In a previous paper (SPE 17163), a v-shape Gas-Water-Ratio (GWR) was observed and discussed from eight wells completed in the Horn River Basin, based on which the flowback data were divided into Early Gas Production (EGP) and Late Gas Production (LGP). The negative sloping GWR observed during EGP was assumed to be a ‘fracture cleanup’ period with negligible influx from the matrix system and a closed-tank model was developed for the fracture system to analyze flowback data. However, the effective fracture network is actually an open system which allows fluid influx from the surrounding matrix blocks. In this paper, we extend the previous model by considering the effect of gas influx during EGP.
Analyzing flowback data requires challenging mathematical procedures, which in most cases are still insufficient to capture the complexity of the two-phase flow in the fracture network. Material Balance Equation (MBE) is a simple but convincing tool in that it eliminates the assumptions lying in the flow equations. This paper seeks to use the MBE technique to analyze early-time two-phase flowback data in shale gas reservoirs. Diagnostic plots from field production data show an immediate gas breakthrough and a negative GWR trend at the beginning of flowback, which indicate the presence of initial gas in the fractures before opening the wells. Based on this observation, we develop a model to describe gas and water production during the early hours of flowback. The early-time two-phase production comes from an ‘effective fracture system’ initially saturated with gas and water. The model considers four drive mechanisms including gas expansion, water expansion, fracture closure and gas influx from matrix. Further, we propose a procedure to analyze field data using different forms of MBEs. It allows the estimation of the effective fracture volume which is difficult to measure in field cases. Finally, we demonstrate the application of the proposed material balance model by analyzing flowback data of one well completed in the Horn River Basin.
Bough, Max (Chevron U.S.A.) | Orrego, Yamila Antonieta (Chevron U.S.A.) | Waldner, Leon Ben (Nexen Energy) | Sheth, Ketan K. (Baker Hughes - Centrilift) | O'Bryan, Roshani (Baker Hughes - Centrilift) | Jankowski, Todd A (Los Alamos National Laboratory) | Pregner, Coyne (Loa Alamos National Laboratory)
Extending system run life impacts well profitability by cutting artificial lift replacement costs and reducing production losses from downtime. The run life of Electrical submersible pumping (ESP) motor can be increased by reducing the operating temperature of the motor. On the other hand, cooler-running motors can be used for high-temperature wells, where downhole temperatures may be a limiting factor.
Controlling motor temperature is important for increasing ESP run life as motor temperature plays a key role in motor failures. Power losses in ESP motors were analyzed for various operating conditions. Power losses are the source of heat generation and the resulting temperature rise in the ESP motor. The internal motor temperature depends upon heat generation in the motor, well parameters, operating conditions, as well as the design and materials used to manufacture the motor.
To reduce internal operating temperature, the motor should efficiently transfer the heat generated within the motor to the well fluid. New techniques for efficient heat transfer were developed and ESP motors with an enhanced motor-cooling design were built. These modified motors were tested in wells under controlled conditions in Claremore, Oklahoma and in two field trials in conventional and SAGD wells. The results showed a significant decrease in the internal operating temperature. This paper will address various contributing factors affecting motor internal temperature, an enhanced cooling design, and field trial test results.
Chevron is a major operator of Electrical Submersible Pumps with a number of global operations where ESPs are the primary means of artificial lift. ESP failures constitute a significant cost in work-overs, resources and deferred production. A 2007 company-wide analysis of ESP failures concluded that motor reliability, and motor cooling specifically is of significant focus to the company in its effort to improve ESP reliability and reduce associated operating expenses (OPEX). Additionally, higher rating for ESPs for thermal operations was identified to be of value.
In 2007, in a joint development effort between Chevron, Los Alamos National Laboratory (LANL) and Baker Hughes (collectively, “Participants”), a project was set up to identify, test and commercialize motor cooling technologies for application throughout Chevron’s operations. The objectives of the project were to find ways to remove internal motor heat to:
In oil sands in situ operations using steam-assisted gravity drainage (SAGD), achieving effective communication between the injector and producer with a reasonable conformance is crucial for the success of SAGD conversion and the following ramp-up phase. The start-up operation normally relies on heat conduction phenomena for establishing communication between the wells. For oil sands reservoirs containing extremely high viscosity bitumen, establishing the temperature profile required for SAGD conversion using conduction as the only heating mechanism is not efficient and can take 90 to 120 days to achieve. Start-up operation can be accelerated by enhancing the rate of convective heat transfer to the formation by techniques such as bullheading and cold/hot dilation.
At Nexen’s Long Lake in-situ SAGD project, the use of higher injection pressures to enhance start-up is limited by the presence of high water saturation zones within the bitumen pay zone (“lean zones”), an adjacent Quaternary-age fresh water-bearing channel, and shallow formation depth. In order to overcome these constraints, an approach using solvent injection in a warm system with enhanced injectivity was successfully designed and implemented. In this approach, the solvent was injected in a high bitumen saturation system after circulating the well for about 70 days. Then, the solvent was chased with hot water into the formation to deliver the solvent deeper into the formation and enhance the rate of solvent-bitumen mixing during the soaking time.
This paper reviews the design criteria, well selection process, and implementation of warm solvent injection in the conducted pilot in the start-up phase of Pad 13 at Long Lake. It also compares production responses of solvent-treated and control wells with comparable reservoir properties within the same pad to evaluate the performance of the designed pilot. Review of the production data shows that the solvent-treated well pair has outperformed all the other well pairs of the pad with no apparent conformance issues. This well had a quick ramp-up which is considerably faster than the average ramp up time at the Long Lake project. The collected data suggests that applying solvent-assisted start-up in systems that have enhanced mobility by pre-circulation of steam can shorten the circulation time and accelerate the ramp-up phase after SAGD conversion.
Quantitative appraisal of different operating areas and assessment of uncertainty due to reservoir heterogeneities are crucial elements in optimization of production and development strategies in oil sands operations. Although detailed compositional simulators are available for recovery performance evaluation for SAGD, the simulation process is usually deterministic and computationally demanding, and it not quite practical for real-time decision-making and forecasting. Data mining and machine learning algorithms provide efficient modeling alternatives, particularly when the underlying physical relationships between system variables are highly complex, non-linear, and possibly uncertain.
In this study, a comprehensive training set encompassing SAGD field data compiled from numerous publicly-available sources is studied. Exploratory data analysis is carried out to interpret and extract relevant attributes describing characteristics associated with reservoir heterogeneities and operating constraints. Because of their ease of implementation and computational efficiency, knowledge-based techniques including artificial neural networks (ANN) are employed to facilitate SAGD production performance prediction. Predicting (input) variables including porosity, net-to-gross ratio, saturation, gross pay, normalized shale barrier thickness and distance to well pair, and initial production rate are formulated. Measures such as cumulative production over discrete time intervals are considered as prediction (output) variables. Data records that are comprised of both input and output variables are assembled; the network is trained using the data set to identify all significant patterns and relationships that exist between the input and the output variables. The model is subsequently validated using a cross-verification procedure, during which records that have been excluded at the training stage are presented to the model.
This paper demonstrates that knowledge-based techniques can be implemented in a practical manner to analyze large amount of competitor data efficiently. The approach can be integrated directly into most existing reservoir management routines. It can also be readily updated when new information has become available. Given that robust reservoir management and real-time decision-making are major challenges faced by the industry, the data-driven models presented in this paper has great potential to be applied in other recovery projects such as solvent-aided steam injection.