Today, almost half of Western Canada's natural-gas production comes from the Triassic-aged Montney formation, a sixfold increase over the last 10 years while gas production from most other plays has declined. In the last few years, demand for condensate as diluent for shipping bitumen has driven development of liquids-rich Montney natural gas leading to a surge in gas production and gas-on-gas competition in the Western Canadian Sedimentary Basin (WCSB), which has driven local natural gas prices down. This has had a material effect on the operations and finances of companies active in the Western Canada and is reshaping the Canadian gas industry. A significant portion of this growth has taken place in NE British Columbia and with the planned electrification of the industry in British Columbia, including the nascent LNG operations, will influence tomorrow's power industry in this region. NE British Columbia is a geographically large area with sparse population and the power supply into this region has lagged behind development of oil and natural gas resources. The area was originally served from geographically closer NW Alberta. More recently, supply was established from the BC Hydro power grid with the most significant developments being Dawson Creek-Chetwynd Area Transmission (DCAT) completed in 2016 and the additional 230 kV transmission projects scheduled for completion in 2021.
Objectives/Scope: In order to maximize the recovery of hydrocarbons from liquids rich shale reservoir systems, the cause and effect relationships between production and the stimulation methods need to be clearly understood. In this study, we utilize multivariate regression models to narrow down the variables in flow simulation models and their range. We then use the flow simulation model to understand the fractured well production behavior and field wide well performance in a liquids rich petroleum system in the Duvernay Basin.
Methods, Procedures, Process: Statistical models assume no physical relationship between the model parameters and the response variable, which in this case is produced volumes over a period of time. On the other hand, simulation studies incorporate physical mechanisms of flow to model and predict the production behavior. The simulation models, however, fall short of incorporating all the mechanisms contributing to the production behavior in the complex shale gas reservoir. Thus there is a need for integration of statistical approaches of understanding production behavior along with physics based model and simulation approach. We use the statistical methods to identify the important physical mechanisms that control the production.
Results, Observations, Conclusions: Multivariate linear regression analysis of the 6 month produced volume and its relationship with parameters such as fracture fluid volumes used, proppant weight placed, number of stages fractured provides a model with reasonably good correlation. The 6 month produced volumes correlate with large proppant weights, lower fluid placements and greater density of fracture stages. Use of Random Forests machine learning algorithm on the dataset confirms that the total proppant placed, well length completed with fractures have high importance coefficients. In order to examine the well performance using full physical models, fractured well simulations are performed on particular wells using the trilinear model. The trilinear model predictions are then compared against other production analyses and the regression model results for consistency. The models showed that in the absence of stress dependent permeability, the production forecast was much higher. Thus, stress dependent permeability appears to be an important factor in the modeling and prediction of production from liquids rich shale reservoirs.
Novel/Additive Information: In this study we describe a method to understand the production data from a liquids rich shale reservoir, by integrating multivariate linear regression analysis, machine learning algorithms along with physical model simulations. The results are novel and offer a method to validate either approach to understand cause and effect relationships. This approach may be classified as a new hybrid modeling workflow that may potentially be used to optimize stimulation techniques in liquids rich shale reservoirs.
Quintero, Harvey (ChemTerra Innovation) | Farion, Grant (Trican Well Service LTD.) | Gardener, David (ChemTerra Innovation) | O'Neil, Bill (ChemTerra Innovation) | Hawkes, Robert (Trican Well Service LTD.) | Wang, Chuan (ChemTerra Innovation) | Cisternas, Pablo (American Air Liquide) | Pruvot, Antoine (American Air Liquide) | McAndrew, James (American Air Liquide) | Tsuber, Leo (Badger Mining Corporation)
This study aims to demonstrate the true benefit of an innovative salt tolerant high viscosity friction reducer (HVFR) that excels at promoting extended proppant suspension and vertical distribution into the fracture when it is used as a base fluid for the Capillary Bridge Slurry (CBS) and other conventional fracturing fluid systems in combination with nitrogen.
The completion of super-lateral wells now being drilled in tight oil and gas shales in North America, with record lengths close to 4 miles, demand for greater carrying capability of low viscosity (slickwater) fracturing fluids, where significant sand settling can occur before the proppant even reaches the fractures. This has sparked recent interest in the development and application of salt tolerant polyacrylamide-based friction reducers, referred to as High Viscous Friction Reducers (HVFR). The downfall of these first generation HVFR's is the lack of compatibility with high salinity brines such as recycled and flowback water, and diminished ability to reduce friction pressure during hydraulic fracturing treatments when compared to industry standard FR's.
Herein, we report the field application of a unique salt tolerant HVFR (HVFR-ST), that consistently provides higher viscosity values (corresponding industry standard HVFR loading comparison) when tested in brines, without sacrificing friction reduction effectiveness. Additionally, a new concept of fracturing fluid referred to as Capillary Bridge Slurry (CBS) has been successfully implemented in North America, where through a surface modification to the proppant, the addition of a gas phase such as N2, and the use of a polyacrylamide-based friction reducer, the proppant becomes part of the fluid structure and is no longer the burden to be carried. The combination of HVFR's and the surface modified proppant can effectively combat the issues faced with proppant transport in long laterals.
This paper will highlight the results on the analysis of the governing proppant transport mechanisms (suspended and bed) of CBS system formulated with HVFR-ST, in the presence of nitrogen (N2), where no detrimental effect in the average distance traveled of the sand particle in the Proppant Transport Test Bench (PTTB) was observed when the brine concentration of the base fluid was increased from 1% to 5% in comparison to industry standard HVFR (HVFR-FW).
Field production data on wells stimulated with CBS show a significant upside (~ 50%) in liquid hydrocarbon production than offsetting wells over a ~ one year period of time.
Friction loop data carried out at 45 L/min (11.89 gals/min) flow rate in an internal diameter pipe of 0.305" shows a reduction on friction pressure in excess of 70%, when HVFR was tested in 5% API brine (4% (w/v) NaCl and 1% (w/v) CaCl2·2H2O) at loadings as low as 0.1%. Furthermore, dynamic measurements within the viscoelastic regime/behavior of the HVFR at different loadings in the oscillatory viscometer will provide learnings on the elasticity-proppant transport relationship of the different fracturing fluid systems.
Through the use of laboratory testing and field study cases, this paper will illustrate the true benefits on the use of salt tolerant HVFR's as a base fluid with the increasing demand of re-cycled and flowback water use in fracturing fluid systems.
Ryan, M. (Baker Hughes, a GE Company) | Gohari, K. (Baker Hughes, a GE Company) | Bilic, J. (Baker Hughes, a GE Company) | Livescu, S. (Baker Hughes, a GE Company) | Lindsey, B. J. (Baker Hughes, a GE Company) | Johnson, A. (Murphy Oil Company) | Baird, J. (Murphy Oil Company)
Development of unconventional reservoirs in North America has increased significantly over the past decade. The increased activity in this space has provided significant data with respect to through-tubing drillouts which had previously not been attainable. This paper is focused on using the field data from the Montney and Duvernay formations along with laboratory data and numerical modeling to understand the hole cleanout associated with through-tubing drillouts of frac plugs.
Initially, an extensive full-scale flow loop laboratory testing program was conducted to obtain data on debris transportation for hole cleanout during through-tubing applications. The testing was conducted on various coiled tubing (CT)-production tubing configurations using various solid particles. The laboratory data was used to develop empirical correlations needed for a transient debris transport model. This model was then used for frac plug drillouts to ensure successful hole cleaning in actual field applications. Computational fluid dynamics (CFD) modelling was also used to further understand and quantify the differences between the laboratory data, field data and transient debris transport model results.
The objective of the work conducted was to gain a better understanding of debris transport and validate the empirical modelling approach developed for hole cleaning. The validation process was conducted in several stages. The first stage was to validate the laboratory data against the Montney and Duvernay field data. The second stage was to verify the results obtained from the empirical model against the results obtained from a computational fluid dynamic model. The results from both modelling approaches were lastly compared to the field data. All these results challenge the current industry's understanding and best practices for through-tubing drillouts in the Montney and Duvernay formations. With the contentious increase of lateral lengths and higher stage counts, the process of drilling out frac plugs has become more complex. This study explicitly benefits all operators in their ever-increasing need to understand their frac plug drillout operations to ensure efficient, cost effective, and most importantly, consistent and repeatable results.
While efficient results for frac plug drillout operations have been accomplished to date, the on-going feedback from the field has been the requirement to produce repeatable drillouts. This paper is the first to show a holistic approach for obtaining a transient debris transport model used for through-tubing drillouts of frac plugs. The novelty also consists of the transient debris transport model validation through laboratory data and actual Montney and Duvernay field data.
This paper outlines methods to characterize hydraulic fracture geometry and optimize full-scale treatments using knowledge gained from Diagnostic Fracture Injection Tests (DFITs) in settings where fracturing pressures are high.
Hydraulic fractures, whether created during a DFIT or larger scale treatment, are usually represented by vertical plane fracture models. These models work well in a relatively normal stress regime with homogeneous rock fabric where fracturing pressure is less than the Overburden (OB) pressure. However, many hydraulic fracture treatments are pumped above the OB pressure, which may be caused by near well friction or tortuosity but, may also result in more complex fractures in multiple planes.
Procedures are proposed for picking Farfield Fracture Extension Pressure (FFEP) in place of conventional ISIP estimates while distinguishing between storage, friction and tortuosity vs. fracture geometry indicators.
Analysis of FFEP and ETFRs identified in the DFIT PTA analysis method combined with the context of rock fabric and stress setting are useful for designing full-scale fracturing operations. A DFIT may help identify potentially problematic multi-plane fractures, predict high fracturing pressures or screen-outs. Fluid and completion system designs, well placement and orientation may be adjusted to mitigate some of these effects using the intelligence gained from the DFIT early warning system.
A single-point entry completion architecture has been implemented in several hydraulically stimulated resource plays across North America. The objective is to understand whether the innate properties of the rock and what we can diagnose about how it hydraulically fractures can inform the question of applicability of single-versus multi-point completion designs.
Wells were treated using a single-point entry design in the Montney and the Duvernay and an assessment of well performance was carried out. Multiple diagnostic pads have been carried out over several years in both formations, including microseismic and geochemical fingerprint data allowing for a general characterization of the gross geometry and connectivity. Initial results from a fiber are available in the Montney with a single point completion design. The fracture diagnostic data was compiled and described in the context of the nine main sub-surface controls on the connectivity.
In the Montney, it is relatively clear how completion intensity changes, like stage length, in single-point entry wells change the production performance outcome. In the Duvernay, there is significantly more uncertainty. This contrast contributed to the decision to treat several follow-up pads in the Montney via a single-point entry design, whereas a multi-point plug and perf completion is preferred for the Duvernay wells. Costs and stage isolation are considerations, but one other contributing explanation is that the dominantly planar fracture geometry in the Montney enables each stage to contribute proportionally, thus ensuring the stimulation distribution effectiveness from the near-to the far-field.
The dry-gas area of the Montney is very stiff, with an absence of natural fractures, a paucity of faults, no containment issues and no significant frac barriers. Conversely, in the Duvernay, the inherent complexity in the fracture geometry complicates the stimulation distribution effectiveness in the far-field. Furthermore, the lower mobility of a liquids-rich hydrocarbon system probably benefits from the potentially tighter frac spacing, possible in a multi-cluster design, even with a probable increase in non-uniformity over single-point.
It is hypothesized that in formations that develop complex fracture geometries, ‘putting all your eggs in one basket’ with a single-point entry design, needs to be assessed along with the other value drivers for the well architecture selection.
This paper presents a hydrocarbon volumetric assessment approach for multiphase reservoirs. The methodology is based upon mass material balance in both gas condensate and wet gas systems and permits for oil/condensate volumetric determination utilizing a novel concept referred to as pseudo formation volume factor (
In conventional oil/condensate volumetric methods, a discontinuity is observed at the boundary between undersaturated gas and oil systems when you move across the mapped phases. The discontinuity results from an inconsistent oil/condensate volumetric approach between oil and gas primary phases. Oil/condensate volumetrics is a function of an oil formation volume factor (
The fundamental assumption in the
The focus of this paper is on Duvernay shale formation in Alberta, Canada. The objective is to provide, based on existing data of production, completion and geological parameters, an automated machine- learning approach to determine the spatial variation in decline type curves for gas production. This model will enable the prediction and uncertainty quantification of production profiles for new target wells or areas in the basin.
The project is based on publicly available monthly production data from most of the producing wells of the Duvernay formation. We use k-means to cluster 273 wells, using geological parameters (thickness, porosity, etc.), completion parameters (horizontal section length, proppant volume, etc.), spatial location, fluid window, and production curves. Based on the clustering results, a machine learning classification is used to draw distinct geographic regions, within which the combination of geological, completion, and production factors is fairly similar. A support vector machine approach is used to create maps of clusters and quantify its uncertainty.
In addition, functional classification and regression trees (CART) is used to indicate the most important/sensitive factors that should be used for clustering.
The results show that the unsupervised method, k-means, performs equally as well as the supervised CART method. The methodology is flexible and allows for quick changes in the variables used in clustering; the transfer to another dataset or basin is straightforward.
Achieving high hydrocarbon recovery is challenging in unconventional tight and shale reservoirs. Although EOR/EGR processes could potentially improve the recovery factor beyond the primary depletion, large-scale field application of these processes are not yet established in these reservoirs. This session will focus on the latest research trends, modelling and experimental work to better understand issues involved in improved economic recovery from such reservoirs.