The objective of this paper is to enhance the produced oil quality during solvent-steam flooding processes by using asphaltenes precipitants and environmentally friendly solvents as injection fluid. This way, it is aimed to increase the asphaltene deposition tendency and decrease the emulsion formation severity.
Eight one-dimensional core flood experiments were conducted; one steam flooding, three solvent flooding, and four solvent-steam flooding. Five different solvents were tested; propane, n-hexane, toluene, Benzoyl peroxide (BP), and a plant-based environmentally friendly solvent (MS). Solvent and water injection, oil and water production, and temperature along the core flood were continuously measured during each experiment. Both produced oil and residual oil samples were further analyzed to investigate the quality of produced oil samples and the amount of asphaltenes deposited on spent rock. An ASTM method which uses n-pentane was implemented to separate asphaltenes from both produced and residual oil samples. The water content of produced and residual oil samples was determined through thermogravimetric analysis (TGA) and the water-in-oil emulsion content of produced oil samples was visualized with an optical microscope. To understand the impact of each SARA (Saturates, Aromatics, Resins, and Asphaltenes) fractions on produced oil quality during solvent-steam processes, every fraction was exposed to liquid or vapor water and examined under a microscope.
It has been observed that stability of asphaltenes and emulsions varies in the presence of vapor or liquid water. Aromatics and Resins fractions are the main contributors of water-in-oil emulsion formation, and emulsion formation is enhanced with the addition of asphaltenes. Vapor-water (steam) promotes the formation of more severe emulsions than liquid-water. Hence, the emulsion formation mechanism was predicted to start with a foam-formation step in where the vapor steam diffuses into the liquid crude before condensing to form liquid water droplets, and then, forming an emulsion at lower temperatures. Since asphaltenes insoluble solvents were used, diffusion of steam occurs mostly in deasphalted oil and mainly in aromatics and resins.
We evaluate the use of facies probability maps for conditioning discrete multiple-point statistical (MPS) facies simulation on dynamic production data. In MPS simulation, conditional probabilities are estimated from a training image (TI), a conceptual model of geologic connectivity, and used to draw samples of facies distributions that are statistically consistent with those encoded in the TI. Whereas conditioning MPS simulation on both static hard data (e.g., well logs) and soft data (e.g., seismic) is straightforward, calibration of facies against nonlinear flow data is nontrivial. The use of facies probability maps for conditioning MPS simulation on dynamic production data presents a promising approach for calibration of complex facies models. We present an overview of MPS-based conditional simulation with probability maps and discuss some of the important properties and implementation issues of this approach. The paper presents two important contributions: (1) improvement of the original probability conditioning method (PCM) by constructing the facies probability maps based on the first and second order statistical moments of the updated permeabilities at each cell; (2) generalization of the "tau" model to include pixel-based τ values that can assign different confidence levels to the facies probabilities at different grid blocks. Results from numerical examples demonstrate that the proposed approach outperforms the original PCM by incorporating additional information from the observed dynamic data into MPS-based facies simulation.
Wang, Y. (China University of Petroleum Beijing) | Cheng, S. (China University of Petroleum Beijing) | Zhang, K. (Lusheng Petroleum Development Co. Ltd SINOPEC Shengli Oilfield Company) | Ayala H., L. F. (Pennsylvania State University) | Qin, J. (China University of Petroleum Beijing) | He, Y. (China University of Petroleum Beijing)
There is growing evidence showing that water injection may induce formation fracturing around injectors in tight reservoirs. Because waterflood-induced fractures (WIFs) are not strengthed by proppants, they close gradually during the field-testing period, which results in "fracture-closure-induced" flow rate, shrinking fracture length (SFL) and decreasing fracture conductivity (DFC). In this paper, we propose a novel semi-analytical model to characterize the BHP behavior of water injectors under the influence of WIF. We consider that pressure losses take place within three sections: reservoir, WIF and wellbore. Flows between reservoir and WIF are linked through a fracture-storage coefficient and fracture-face skin factor, while flows between WIF and wellbore are coupled via wellbore-storage coefficient and choked-fracture skin factor. Finite difference and perturbation theory methods are deployed to include the SFL and DFC effects, respectively. Duhamel principle is invoked to characterize flow rate changes caused by wellbore and fracture storage effects. Results show that bi-storage effects can be identified as two unit slopes in the pressure derivative curve. In the abscense of extra pressure drop between wellbore and WIF, i.e., choked-fracture skin equals to zero, a prolonged storage period with a considerably large storage coefficient can be obtained. In addition, we find that SFL could cause the variable fracture storage effect while DFC may lead to the upward of pressure derivative curve at late times. Finally, the model is successfully applied in the Changqing Oilfield to validate its reliability.
The making of development plan to produce an oil or gas field usually involves several distinct stakeholders (e.g., the operator, partners and the government) with many engineering, economic, environmental, and/or political considerations. The interests of these stakeholders may be potentially in conflict with each other, entailing that a robust development plan should take into account all these concerns. Multiobjective optimization (MOO) can be used to find a set of optimal solutions (i.e., the so-called Pareto front) to balance all these interests. This work reviews and presents several typical applications of MOO to illustrate its value for efficient and robust reservoir management (RM) and asset development. These applications include: (i) simultaneous optimization of oil recovery and unwanted fluids, (ii) states-constrained optimization, (iii) short-term and long-term optimization, and (iv) optimization under uncertainty (OUU) for risk mitigation. Particularly, the MOO solution is compared with a conventional single-objective optimization (SOO) method in handling these problems. Results show that MOO is a solution of choice for comprehensive RM when a project involves optimizing multiple metrics or multiple drivers.
The oil and gas production landscape in North America has seen a paradigm shift since the collapse in oil prices in 2014. Although prices remain challenging, several operators have managed to sustain the relatively long period of low margins through some aggressive approaches. This paper inspects changes in operating strategies and field development plans across all oil-rich basins in the US Rocky Mountain fields and how operators have used a combination of low oilfield service prices, high-graded well locations, and incremental fluid/proppant volumes to increase production.
The paper investigates the transformation in operating philosophies since 2014 in four oil-rich basins in the Rocky Mountain region—Williston, Denver-Julesburg (DJ), Uinta, and Powder River. The Bakken formation in the Williston basin represents one of the best-quality rocks in all of North America. However, high oil-price differentials and well costs have made it difficult for drilling to remain profitable. The core of the DJ basin (Wattenberg) has one of the lowest break-even prices in the region, and rig count continues to increase as operators start seeing signs of recovery in the market. The Uinta basin, although relatively small in size, has shown tremendous return potential in the form of multiple stacked pays and promising production results. The Powder River basin poses one of the toughest operational environments in the region owing to wildlife stipulations, harsh weather, and deeper targets.
High-graded well locations in the Bakken are limited to few fields, which limits the scope of expansion in the current oil price environment. The DJ basin is challenged with high-density well spacing; estimated ultimate recovery (EUR) per drilling spacing unit (DSU) continues to increase, but EUR per well has gone down by as much as 60%. In the Uinta basin, formations never known to be continuous in the Green River group have shown significant return potential. The Powder River basin has recently attracted large investments from major independent operators as they tackle drilling challenges associated with abrasive rocks and testing optimum lateral landing points.
Case studies show how operating strategies have changed with changes in oil prices. The Bakken and DJ basins are relatively mature, and as drilled-but-uncompleted (DUC) inventory continues to increase, depletion from existing wells and interference between fractures is impacting production from new wells. The Powder River basin is still in the exploratory phase, and operators are still working on reducing well-costs, optimizing fracturing-fluid/proppant volumes, and examining productivity of other target rocks. The Uinta basin is in the early phases of expansion, with many of the fields still being explored for scalability. Changes in production maps and completion trends provide a comprehensive understanding of how these variables have impacted oil output from the region since 2012.
Yalgin, G. (Middle East Technical University) | Zarepakzad, N. (Middle East Technical University) | Artun, E. (Middle East Technical University) | Durgut, I. (Middle East Technical University) | Kok, M. V. (Middle East Technical University)
Computationally efficient screening and forecasting tools can offer faster decision-making and value- creation opportunities for enhanced oil recovery (EOR) operations without requiring a high-fidelity reservoir model. In this paper, we present a data-driven modeling approach utilizing numerical models and neural networks (ANN) to screen EOR methods in a rapid way. Numerical modeling is employed to generate the data for the training of the neural-network based data-driven model. It is aimed to develop comprehensive and globally applicable screening tools that can be used to identify reservoirs where the EOR method would be applicable through estimation of performance indicators, such as utilization efficiency. Important process variables related to the EOR method are identified and grouped, while also defining their limits and statistical distributions. A large number of scenarios are generated and run using the numerical model that represents the EOR method under consideration. A simple yet representative performance indicator is defined and calculated for each scenario, which takes into account both additional income due to incremental oil recovery and the cost of the injected agent. Considering annual volumes in the calculation and evaluating the time-dependency of the performance indicator allow to incorporate time-value of the money. Finally, the knowledge base is used to train a neural network that can capture the signatures within the dataset through an iterative training process. This methodology is explained by highlighting important components of the workflow as well as best practices of each step. Results of two example applications are summarized: 1) Cyclic steam injection, 2) Polymer flooding. The results indicated that presented methodology can be successfully followed for different EOR methods. In both cases, the data-driven screening model was able to predict the efficiency indicator within acceptable accuracy levels and identified the degree of success of each method under different reservoir and operational conditions. Comparison of sensitivities between numerical and data-driven models showed that the data-driven model captured the physics of both problems as reflected by the numerical model. Predicting the indicator at 2-year intervals allowed to estimate the feasibility as a function of time.
Fluid diffusivity inversion and injection-induced microseismicity provide useful means of evaluating unconventional reservoirs. When taking into consideration geomechanics, linear poroelasticity equations provide the key connection between diffusion and microseismicity. This work explores microseismicity generation from a probabilistic point of view, embedding uncertainty assessment in its quantification. Bayesian framework serves as the base for probabilistic analysis.
The primary objective of this work is to develop a new microseismicity probabilistic model framework that can be used for uncertainty quantification in data analysis as well as to provide forward modeling of microseismicity. Results are tested against real data of Horn Rives shales in Western Canada, and show good prediction of the number of actual microseismicity occurrences against time.
The novel probabilistic model is derived from Directed Graphic Model using a statistical learning framework. Stochastic Poisson process combined with a specific rate model is integrated to generate a likelihood function. Both, parameter inference and microseismic event forecast are assisted by Bayesian theorem. The model has an intrinsic statistical learning root, which specifically uses observed microseismic data to update model parameters and then is applied for microseismicity prediction.
The model is extended to take into account basic geomechanical principles.
The novelty of this study is the development of a probabilistic microseismic prediction model which obeys rate-and-state law based relative seismicity rate constitutive equations. The model inherently considers time dependence of nucleation and fault geomechanics. It can be used for planning purposes in the pre-hydraulic fracturing stage.
Quintero, H. J. (Trican Well Service Ltd.) | Mattucci, M. (Trican Well Service Ltd.) | O'Neil, B. (Trican Well Service Ltd.) | Folkes, G. (Trican Well Service Ltd.) | Zhang, K. (Trican Well Service Ltd.) | Wang, C. Z. (Trican Well Service Ltd.) | Lu, W. (Trican Well Service Ltd.)
The development of tight oil and gas shale relies heavily on multi-staged hydraulic fracturing, with the objective being to induce a complex network of interconnected fractures (artificial and natural), effectively created by water-like viscous fluids and sand laden slurries injected at very high pressures and rates.
Numerous methods have been employed to reduce sand settling and duning during hydraulic fracturing. Conventionally, frac designs have relied on injection rate, and viscoelasticity of the fluid to offset sand, or proppant settling. As of late, development in proppant technologies have focused on introducing alternative engineered materials for proppants that feature oil field brine pseudo specific gravity (S.G.), while maintaining mechanical strength, therefore relying on the buoyancy effect for proppant transport; despite all these efforts, proppant suspension remains a burden for the fracturing fluid.
Herein, we report a pioneering fracturing fluid where through inducing capillary bridges proppant sands become part of the fluid structure and are no longer the burden to be carried. This new fluid system offers a unique and superior proppant transport mechanism, under a wide range of shear stress and rate conditions, without the need for conventional polymers and/or cross-linkers.
This field-proven and cost-effective fracturing fluid features a non-damaging synthetic polymer. Field cases show successful placements of proppant where other conventional fracturing fluids have failed/screened-out.
Regained permeability analysis indicates ≥100% regained permeability when Bandera sandstone (~1 - 10 md permeability) core samples were tested. Proppant settling test analysis showed no proppant settling in a 5 hour period when 500 kg/m3 (4.17 lb/gal) of 30/50 U.S mesh size proppant laden slurry was tested, simulating a bottomhole temperature (BHT) of 70°C (158°F). Also, a more than 33% increase in sand pack volume in the slurry was observed during the aforementioned analysis when compared to a borate-crosslinked guar slurry counterpart.
This paper intends to detail the development, laboratory testing and field cases of this novel fracturing fluid, that has been successfully pumped in more than 150 frac stages in the Western Canadian Sedimentary Basin (WCSB).
Optimizing a well's hydraulic fracture design within a pad development environment is a multi-disciplinary effort and requires a 4-dimensional understanding of the reservoir. This paper presents a workflow that uses an integrated workflow that combines geology, and geomechanics to build a reservoir model which can be interrogated and updated with a geologically and geomechanically constrained grid-based 3D planar frac model and production simulation using a fast marching method. In this case, as applied to an Eagle Ford well to address concerns of completion optimization, production and depletion forecasting, well spacing and well interference.
The workflow captures the variability of stresses and rock properties along the wellbore and around it by using multiple geologic and geomechanical approaches. The estimated variability of rock mechanical properties is used as input in a 3D planar frac simulator. An alternative approach to geoengineering a completion, using the differential stress derived from geomechanical simulation that overcomes the limitations of well centric methods, is also illustrated.
The frac design results are used as inputs/constraints in a new reservoir simulator that was developed using the Fast Marching Method to estimate drainage area. This allows for a constrained, yet extremely fast estimate of the EUR and resulting pressure depletion, addressing the important concerns of well spacing optimization and prevention of frac hits and well interferences, all in a timely manner.
The integrated approach facilitates adaptive frac design which honors in-situ conditions including stress field heterogeneity, stress shadow effects and the pressure depletion from nearby producing wells. The proposed workflow enables greater investment efficiency and promotes field development optimization.
Steam-Assisted Gravity Drainage (SAGD) is widely used in Alberta for recovering bitumen from oil (tar) sands. A variation of the same has had some success in heavy oils as well. It is a high-risk recovery method and requires careful planning and design. This paper outlines the success criteria for SAGD, and a design methodology.
First of all, applicability of other lower risk recovery processes, such as steamflood variants, is considered to determine if SAGD is a good choice. SAGD has been successful in oil sands of Alberta under rather restricted conditions. Geology is the most important factor, in particular vertical permeability, oil saturation, and initial mobility of water. Where the minimum criteria are not satisfied, there have been failures, discussed also. The author has developed new equations for the entire SAGD process, not just the stabilized oil flow regime, given previously, and has corrected the errors in the same. These are discussed in detail, with examples. The application of SAGD variations in conventional heavy oils is also considered.
The current experience in Alberta, and elsewhere, is described, and reasons for success/failure are outlined. Given that background, the desirability of SAGD vis-à-vis other thermal processes is discussed for California heavy oils. The variation of SAGD being employed in Saskatchewan heavy oils is also discussed, showing that it is not SAGD in the strict sense, rather a modified steamflood, using horizontal wells. It is concluded that SAGD has a high oil recovery potential if the right combination of rock-fluid properties is present. The application of SAGD to conventional heavy oils is equally problematic, in view of a very different mechanism.
The novelty of the paper lies in (1) a comprehensive treatment of SAGD, from the rising chamber to plateau to decline phases, (2) assessment of SAGD compared to other recovery methods for different types of reservoirs, and (3) application of SAGD variants to conventional heavy oils.