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Rosenhagen, Nicolas M. (Colorado School of Mines) | Nash, Steven D. (Anadarko Petroleum Corporation) | Dobbs, Walter C. (Anadarko Petroleum Corporation) | Tanner, Kevin V. (Anadarko Petroleum Corporation)
Abstract The volume of stimulation fluid injected during hydraulic fracturing is a key performance driver in the horizontal development of the Niobrara formation in the Denver-Julesburg (DJ) Basin, Colorado. Oil production per well generally increases with stimulation fluid volume. Often, operators normalize both production and fluid volume based on stimulated lateral length and investigate relationships using "per-ft" variables. However, data from well-based approaches commonly display such wide distributions that no useful relationships can be inferred. To improve data correlations, multivariate analysis normalizes for parameters such as thermal maturity, depth, depletion, proppant intensity, drawdown, geology and completion design. Although advancements in computing power have decreased cycle times for multivariate analysis, preparing a clean dataset for thousands of wells remains challenging. A proposed analytical method using publicly available data allows interpreters to see through the noise and find informative correlations. Using a data set of over 5000 wells, we aggregate cumulative oil production and stimulation fluid volumes to a per-section basis then normalize by hydrocarbon pore volume (HCPV) per section. Dimensionless section-level Cumulative Oil versus Stimulation Fluid Plots ("Normalization" or "N-Plot") present data distributions sufficiently well-defined to provide an interpretation and design basis of well spacing and stimulation fluid volumes for multi-well development. When coupled with geologic characterization, the trends guide further refinement of development optimization and well performance predictions. Two example applications using the N-Plot are introduced. The first involves construction of predictive production models and associated evaluation of alternative development scenarios with different combinations of well spacing and completion fluid intensity. The second involves "just-in-time" modification of fluid intensity for drilled but uncompleted wells (DUC's) to optimize cost-forward project economics in an evolving commodity price environment.
Abstract In some basins, large scale development of unconventional stacked-target plays requires early election of well targeting and spacing. Changes to the initial well construction framework can take years to implement due to lead times for land, permitting, and corporate planning. Over time, as operators wish to fine tune their development plans, completion design flexibility represents a powerful force for optimization. Hydraulic fracturing treatment plans may be adjusted and customized close to the time of investment. With a practical approach that takes advantage of physics-based modeling and data analysis, we demonstrate how to create a high-confidence, integrated well spacing and completion design strategy for both frontier and mature field development. The Dynamic Stimulated Reservoir Volume (DSRV) workflow forms the backbone of the physics-based approach, constraining simulations against treatment, flow-back, production, and pressure-buildup (PBU) data. Depending on the amount of input data available and mechanisms investigated, one can invoke various levels of rigor in coupling geomechanics and fluid flow – ranging from proxies to full iterative coupling. To answer spacing and completions questions in the Denver Basin, also known as the Denver-Julesburg (DJ) Basin, we extend this modeling workflow to multi-well, multi-target, and multi-variate space. With proper calibration, we are able generate production performance predictions across the field for a range of subsurface, well spacing, and completion scenarios. Results allow us to co-optimize well spacing and completion size for this multi-layer column. Insights about the impacts of geology and reservoir conditions highlight the potential for design customization across the play. Results are further validated against actual data using an elegant multi-well surveillance technique that better illuminates design space. Several elements of subsurface characterization potentially impact the interactions among design variables. In particular, reservoir fluid property variations create important effects during injection and production. Also, both data analysis and modeling support a key relationship involving well spacing and the efficient creation of stimulated reservoir volumes. This relationship provides a lever that can be utilized to improve value based on corporate needs and commodity price. We introduce these observations to be further tested in the field and models.
Abstract Unconventional completions in North America have seen a paradigm shift in volumes of proppant pumped since 2014. There is a clear noticeable trend in both oil prices and proppant volumes – thanks to low product and service costs that accompanied the oil price crash in early 2015. As the industry continues to recover, operators are reevaluating completion designs to understand if these proppant volumes are beyond what is optimal. This paper analyzes trends in completion sizes and types across all major unconventional oil and gas plays in the US since 2011 and tracks their impact on well productivity. Completion and production data since 2011 from more than 70,000 horizontal wells in seven major basins (Gulf Coast, Permian, Appalachian, Anadarko, Haynesville, Williston and Denver Julesburg basins) and 11 major oil/gas producing formations were analyzed to examine developments in proppant and fluid volumes. Average concentration of proppant per gallon of fluid pumped was used to understand transitional trends in fracturing fluid types with time. Production performance indicators such as First month, Best 3 or Best 12 months of oil and gas production were mapped against completion volumes to evaluate if there are added economic advantages to pumping larger designs. In general, all major basins have seen progressive improvements in average well performance since 2011, with the Permian Basin showing the highest improvement, increasing from an average first-six-months oil production of 25,000 bbl in 2011 to 75,000 bbl in 2017. The Gulf Coast basin, where the Eagle Ford formation is located, has seen a 6-fold increase in proppant volumes pumped per foot of lateral since 2011 while the Permian and Appalachian basins hit peak proppant volumes in 2015 and 2016 respectively. In Permian and Eagleford wells, higher proppant volumes in general have resulted in better production up to a certain concentration. In Williston and Denver basins, most operators are moving away from gelled fluids, and reduced average proppant concentration per fluid volume pumped shows inclination toward hybrid or slickwater designs. While some of these observations are tied to reservoir quality, proppant volumes have begun to peak as operators have either reached an optimal point or are in the process of reducing volumes. Demand for proppant is expected to nearly double by 2020. As oil prices continue to recover, well AFEs continue to increase, despite multiple efforts to improve capital efficiency. The need for enhanced fracture conductivity and extended half-lengths on EURs are been discussed by combining actual observed production data and sensitivities using calibrated production models. The industry is moving toward large-volume slickwater fracturing operations using smaller proppants, but he operating landscape is expected to see a correction when such designs become less economical.
Abstract Accelerating the learning curve in the development of the Vaca Muerta utilizing lessons learned in North American unconventional resource plays is the focus of this paper. Reducing completion costs while maintaining high productivity has become a key objective in the current low-price environment. Completion diagnostics have been demonstrated to optimize stimulation and completion parameters that have shaped successful field developments. The paper reviews stimulation diagnostic data from wells completed in the Tuscaloosa Marine Shale, Eagle Ford, Wolfcamp and Niobrara shale formations. Case histories are presented in which proppant and fluid tracers were successfully employed in completion optimization processes. In the examples presented, diagnostic results were used to assess the stimulation of high productivity intervals within a target zone, evaluate various completion methods, and optimize stage and cluster spacing. The diagnostic data were compared with post-frac production rates in an effort to correlate completion changes with well performance. Results presented compare first, engineered perforations versus conventional geometrically spaced perforations to drive up effectiveness in cluster stimulation. Second, new chemistries, such as nanosurfactant, versus conventional chemistries to cut either completion cost or prove their profitability. Third, employing an effective choke management strategy to improve well productivity. Last, as in any stacked pay, determining fracture height growth in order to optimize well density, well spacing, field development and ultimately the recovery of the natural resources. Completion effectiveness is shown to be improved by landing laterals in high productivity target intervals, increasing proppant coverage across the lateral by utilizing the most effective completion methods, optimizing cluster spacing and decreasing the number of stages to reduce completion costs while achieving comparable production rates. Cluster treatment efficiency (CTE), in particular, has become a critical metric when optimizing hydraulic fracturing treatment designs based on current and future well densities. It can be used to rationalize well performance as well as to identify possible candidates for a refrac program. Using completion diagnostics, successful completion techniques were identified that led to production enhancements and cost reductions in prolific plays such as the Tuscaloosa Marine Shale, Eagle Ford, Wolfcamp and Niobrara.
The Upper Cretaceous Codell and Niobrara formations are primary targets in the Wattenberg field (Figure 1) of the Denver- Julesberg basin in northwest Colorado. Although initial discovery of producible hydrocarbons in the Codell occurred in 1955, it was not until the early 1980s when larger scale completion began for the Codell and Niobrara wells throughout the field. Since the early 1980s, there have been more than 10,000 Codell and Niobrara completions in the Wattenberg field.
Originally, the Codell and Niobrara formations were completed individually within the same well. In the early 1990s, operators introduced a limited-entry style stimulation technique in an effort to effectively stimulate both formations with one hydraulic fracturing treatment. Although there is currently significant activity in the field with regard to horizontal well completion in both the Codell and Niobrara formations, extensive vertical well completion still exists. Various completion strategies are currently employed for vertical well completion, including individual stimulation of the Codell and Niobrara formations, limited-entry completion of both formations, and completion of only one of the producing horizons, leaving the other behind pipe. Furthermore, there are many cases of recompletions where an operator has re-entered a Codell-only well at a later date to complete the Niobrara.
Spatial sampling was employed to assess the effectiveness of various completion strategies in one area of the Wattenberg field. Spatial sampling is a documented method for comparing large groups of wells with their direct offsets. The original intent of the spatial sampling method was to identify underperforming wells; however, the method has also been employed as a way to compare various completion or stimulation techniques.
The Niobrara Shale in the United States has ramped up into a hot play that could soon bring an explosion of horizontal drilling in Colorado and Wyoming. The combination of horizontal drilling and multistage hydraulic fracturing is transforming the Niobrara from a target that has been drilled vertically and primarily for gas for nearly 100 years into a liquids-rich play that is capturing considerable attention. Speaking at the 2011 SPE Annual Technical Conference and Exhibition in Denver, John Ford, general manager of Colorado’s Wattenberg field at Anadarko, described the growing Niobrara activity as “really the next big thing.”
That optimism was understandable. In November, Anadarko announced that its leases at Wattenberg may hold more than a billion barrels of recoverable oil and natural gas. The statement noted company drilling success in 11 recent wells at the field, including the Dolph 27-1HZ horizontal well that showed initial production of more than 1,100 B/D of oil and 2.4 MMcf/D of natural gas. These latest wells have given the company confidence that it can drill between 1,200 and 2,700 wells in northeast Colorado, with approximately 160 wells planned for this year. Based on results so far, the company expects ultimate recovery of between 500 million and 1.5 billion bbl of oil, natural gas liquids, and natural gas on an equivalent basis.
Anadarko is not alone. Chesapeake Energy, Noble, Encana, and EOG Resources are among the largest acreage holders and the most active drillers of many companies—including numerous small independents—probing the Niobrara. Majors such as Shell and Marathon Oil have significant acreage.
There are more than 50 operators in or near the Wattenberg field alone. Situated north/northeast of the Denver area, Wattenberg is the largest producing field in the Denver-Julesburg (D-J) Basin and one of the largest onshore oil and gas fields in the US.
Reservoir Rock and Producing Regions
Although the Niobrara is usually referred to as a shale, its reservoir rock consists primarily of limestone or chalk intervals, said Steve Sonnenberg, professor of petroleum geology at Colorado School of Mines in a recent edition of the AAPG Explorer (published by the American Association of Petroleum Geologists). “The formation demonstrates facies changes that range from limestone and chalk in the eastern end to calcareous shale in the middle and eventually transitioning to sandstone farther west,” said Sonnenberg, a past president of AAPG. “Depth and thickness are highly variable.”
The Codell formation is a low permeability, clay rich, late Cretaceous agesandstone within the Wattenberg field of the DJ Basin. Since 1997 over 1500Codell wells have been restimulated. Results on the past 200 refractured Codellwells using a reduced CMG polymer fluid system have yielded incremental monthlyproduction results in excess of 1900 BOE/well or approximately 80% of theoriginal initial production. Success of this program is believed to be thecombination of stringent well selection criteria, high fluid quality controlguidelines and effective operational field practices. It is believed that dueto this recent success in restimulating the Codell, over 4000 additional wellswithin the DJ Basin may be restimulated with economic benefits.
This paper will discuss completion history of the Codell formation and howcriteria from candidate selection to fluid quality may impact the success ofsuch a program.
Records indicate that the first Codell completion in the Wattenberg field ofthe Denver-Julesburg basin occurred in 1955. It was not until the early 1980'sthat the Codell became a major gas play. Since that time thousands of Codellwells have been developed within an area of approximately 100,000,000acres.1 The DJ basin shown in Figure 1 is an asymmetricalbasin just north of Denver, Colorado with the axis of the basin runningparallel to the Front Range uplift.
The Codell, described as Type 2 sandstone by Weimer andSonnenberg2, is a member of the Upper Cretaceous Carlile shale. Itis a bioturbated, reworked fine-grained marine shelf sandstone without acentral bar facies and is laterally continuous across the field area. Figure2 is a stratigraphic sequence of formations bounding the Codell within theDJ Basin. Over the years, many wells have included the Niobrara formation bymeans of separate completions on both the Niobrara and Codell or simultaneouslystimulating both formations with limited entry techniques.3Production from the Niobrara often times has proved to be limited due tonanodarcy matrix permeability. Due to the Niobrara inconsistency, a greatnumber of wells were completed solely in the Codell interval.
These reservoirs were initially over pressured with a pore pressure gradientof ±0.60 psi/ft.4 Pay thickness in the Codell can range from 14 to20 ft. within the central portion of the basin at typical depths of 7000 - 7200feet. Bottom hole temperatures are generally between 230-250° F BHST. It is aclay rich sandstone (15-25% by volume) with pore filling and pore lining mixedlayer illite/smecite clays. Permeability is low (i.e., <0.1 millidarcies),with Density log measured porosity ranging from 8 to 20%.
Aggressive exploration and development of the Codell led to severalexperimental completion techniques throughout the years. Wells were stimulatedwithout regard to geological and lithologic variations. A wide range of fluidtypes and treatment designs were implemented in order to achieve an economicalrate of return.
Original Codell Completions
An obvious contributor to the potential for restimulations is the originalcompletion. The Codell formation has a history that begins in the middle 1950'sand continues today with the continued drilling of acreage within the DJ Basin.Original completion techniques and stimulation fluids utilized have affectedthe results of restimulation programs.
A statistical study of "J" and Codell wells in the Denver-Julesburg (D-J) Basin was undertaken to determine which parameters influence well productivity. The parameters reviewed were open hole logging parameters and operational parameters. Parameters such as zone thickness, porosity, water saturation, shale indicators and the size of the hydraulic fracture treatment were reviewed. These parameters were chosen because they: 1) may be related to well productivity; 2) are easily obtainable from productivity; 2) are easily obtainable from public sources; and 3) are related to public sources; and 3) are related to theoretical hydraulic fracture models.
A non-linear multi-variate regression analysis was used in this study. The variables used in the regression analysis can be related to the variables in the "uniform flux fracture" model.
The results of the regression analysis can be used; 1) to determine which parameters are most correlative to well productivity, 2) to determine the relative magnitude of the parameter's influence and 3) the degree of certainty of the correlation.
The application of regression analysis determined which log characteristics are correlative with well productivity, quantified the influence of each parameter and quantify the degree of uncertainty. Regression analysis can be applied to reservoirs which are not amenable to conventional analysis.
Deterministic models and empirical correlation are the two most common methods to determine well productivity. With the advent of personal computers and statistical software, under utilized, but very powerful statistical methods, such as regression analysis should become more popular. Regression analysis offers a reliable method for determining well productivity.
Reservoir simulators are deterministic models. The major difficulties with deterministic models are: 1) verifying that the model accurately simulates the physical process and 2) measuring the variables which process and 2) measuring the variables which are input into the model. Different models simulating the same process have been offered, these models vary in the degrees of sophistication and accuracy of their results. Many variables which are used in hydraulic fracture reservoir simulators, such as far field stresses and permeability of the sand pack are not measured on a routine basis and may never be measured with any degree of certainty.
Empirical correlation such as hyperbolic decline curve fitting were developed by utilizing historical performance without attempting to determine the underlying factors causing such behavior. Often empirical models have gone awry when the factors causing the historical performance are not present in the case to which they are applied. Anecdotal inference is a form of empirical correlation. Statement such as "you need ten feet of pay to make a well ....." or "our fracture performance is better because..... " are examples of anecdotal inference.
A case study comparing the performance of wells fractured with crosslinked guar and hydroxypropyl guar (HPG) is presented. Data indicates that for a given crosslinked system, guar and HPG polymers yield comparable proppant pack impairment and fracture polymers yield comparable proppant pack impairment and fracture conductivity. Detailed laboratory conductivity and well performance data are presented for both low and high temperature conditions. Laboratory conductivity data is reported for proppant placed with guar and HPG crosslinked fracturing fluids under in-situ conditions. The effects of proppant embedment. the gel filter cake, and long-term exposure to reservoir temperature and closure stress were determined in this study. Additionally, the effect of crosslinker, breaker system, and polymer load on fracture conductivity is discussed in detail. Subsequent to laboratory testing, numerous fracture design and production simulations were performed to determine the effect of production simulations were performed to determine the effect of guar and HPG crosslinked fluids on well performance. The data indicates the forecasted cumulative production of wells fractured with guar and HPG are similar. However, due to the relatively lower cost of guar, the Net Present Value (NPV) of wells fractured using guar is greater due to lower treatment costs. A case study of sixteen high-temperature wells located in Weld County, Colorado was performed to determine the "actual" effect of the fracturing fluid on well performance. A comparison of post-frac well production data indicates guar and HPG crosslinked fluid yield comparable proppant pack impairment, and thus similar well performance. A detailed discussion is presented. performance. A detailed discussion is presented
Previously researchers have reported natural polymers utilized in Previously researchers have reported natural polymers utilized in water-based fracturing fluids have adverse effects on proppant permeability. However, these viscous fluids provide an permeability. However, these viscous fluids provide an efficient means to create and propagate a fracture, and effectively transport proppant into the created fracture. Thus, it would be beneficial to develop methods to minimize proppant permeability impairment caused by the polymers. One of the earliest attempts to decrease proppant permeability damage was directed at the development of a "cleaner" polymer system. Guar, a naturally occurring polysaccharide, was reacted with proplylene oxide to form HPG. During this process, a large quantity of plant material (residue) was removed to yield a "cleaner" polymer. Laboratory tests indicated that HPG had only 1 to 3 weight percent (%w/w) residue, whereas guar exhibited 8 to 13 % w/w residue. Based on this information, it was concluded that HPG creates less proppant pack damage than guar polymers. Additionally, HPG offered improved compatibility with methanol and greater high-temperature stability. Consequently, in the early 1970's, the fracturing industry became very conscious of the fact that HPG had a lower residue than guar. Usage of guar fracturing fluids decreased dramatically (Fig. 1) while HPG usage increased. Thus, guar was perceived to be a "dirty" fluid and HPG became the standard frac fluid polymer. In 1984 a conductivity study was performed by Almond and Bland that indicated no correlation could be drawn between % w/w residue and proppant pack permeability impairment. In fact, it was reported that guar and HPG produced similar proppant pack damage (18 % HPG vs. 20 % guar @ 120 degrees F), even though the intermediate residue guar had 5 to 6%w/w residue compared to HPG's 1 to 2%w/w residue. Recently, conductivity studies performed under in-situ conditions by Pennys have shown that both guar and HPG yield similar conductivity impairment. Additionally, Penny's study indicates that polymer loading, type of crosslinker, and breaker system dramatically affect the conductivity of a proppant pack. In today's oilfield environment with depressed hydrocarbon prices, the optimization of all costs associated with the production prices, the optimization of all costs associated with the production of oil and gas is required. Since the fluid polymer costs may constitute 15 to 20% of hydraulic fracturing costs, guar warrants reevaluation as a cost effective alternative to more expensive, so-called "cleaner" polymers. This paper presents the results of extensive laboratory conductivity testing of proppants placed with various guar and HPG crosslinked systems. The laboratory data is supported by a case study of 16 wells fractured with guar and HPG crosslinked systems.