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Travers, Patrick (Dolan Integration Group) | Burke, Ben (HighPoint Resources) | Rowe, Aryn (HighPoint Resources) | Hodgetts, Stephen (Dolan Integration Group) | Dolan, Michael (Dolan Integration Group)
Abstract Scope: The management, treatment and disposal of hydraulic fracturing flowback fluids and produced water presents a major challenge to operators. Though the volumes of water are tracked closely during operations, the sources of that water are not well understood. The objective of this study is to apply a cost effective and proven technique, stable isotope analysis, along with an extensive sampling program (n>1,500 samples) to describe the contributions of variable water sources through completions, flowback and the production lifecycle of multiple horizontal, hydraulically fractured wells in the Denver Basin, Colorado. Methods: The water stable isotopes of hydrogen (H and H) and oxygen (O and O) are conservative tracers and particularly advantageous because they occur naturally in these systems and rely on well-established scientific and analytical techniques. Sample collection is simple and does not require specialized equipment or operational downtime. 80 horizontal, hydraulically fractured wells completed in the Cretaceous Niobrara or Codell Formations were selected for this study. More than 1,500 samples were collected and analyzed in total, including: baseline samples of the source water used to stimulate the well, time series samples collected at daily or semi-daily intervals during the early weeks of flowback, and samples collected several months after the wells were brought on production. Samples of produced water were also collected from legacy wells in the field as well as offset wells being monitored for frac hits during completions. Results: Samples of the near surface and shallow aquifer source water collected prior to hydraulic fracturing fell on or near the global meteoric water line (GMWL) as defined by Craig (1961). This isotopic signature is expected for modern water in aquifers charged by precipitation. In contrast, samples collected during flowback and production were significantly enriched in H and O. Furthermore, the magnitude of the isotopic difference between the source and flowback water increased with time until equilibrating after several months. This equilibrated composition is consistent for Niobrara and Codell wells in the field, as well as legacy wells sampled and consequently is hypothesized to be indicative of native formation water. The study did find exceptions, particularly with wells known to be connected to major fault or fracture networks. These samples deviated from typical formation water signatures, potentially indicating the migration of deeper sourced fluids or the vertical mixing of shallower fluids with Cretaceous waters. Significance: The scale of this study is unique in the literature and provides novel and comprehensive insight into the dynamics of flowback and the sources of produced water in the Denver Basin. This study demonstrates that these data can clearly differentiate water injected during stimulation from native formation waters, as well as track the magnitude and duration of well cleanup. It can also identify wells that may be producing water with a unique composition due to fluid migration through faults or fracture networks or due to nearby well communication.
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.
Summary 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.
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.
Abstract In unconventional resource plays, constructing a sound geological model that ties various well information is imperative for properly extracting and integrating well and seismic information and for predictive and prescriptive analytic workflows. Unlike conventional plays, unconventional plays that span basins have potentially tens of thousands of wells. Constructing geological models to include all wells and then updating them as additional ones become available can be a daunting task. When constructing large cross sections, regional stratigraphic patterns are easily discernible visually. Converting these geologic events and spatial patterns to digital information using the power of the computer and new machine learning techniques is becoming more important than ever as geoscientists attempt to "keep up" with all this information. This paper will cover a modern technology toward that end. Introduction Previous attempts have been made to pick geologic well tops automatically using expert systems (Olea et al.), neural networks (Luthi et al.), and dynamic programming (Lineman et al., Inazaki, Zoraster et al., Fang et al.). While these previous efforts have been helpful in defining the problems and building blocks to solve well-log correlation automatically, they have clearly been much less successful than has been observed in seismic picking algorithms that started in the 1980's. This is mainly owing to the nature of seismic data. Seismic traces are band-limited, closely spaced (on the order of meters) with neighboring traces almost identical to each other, and are consistent with the same start and ending times, sample rates, and vertical representation. These traits make correlating neighboring peaks, troughs and zero-crossings reasonably easy as compared to well logs, which are more widely spaced (on the order of hundreds to thousands of meters), have inconsistent depth ranges with possible gaps, and may be from highly non-vertical well bores. As more oil companies transition from exploration to resource recovery optimization and the number of new wells in well-known basins dramatically increases, geologic cross sections across these basins begin to take on more of a seismic look, as shown in Figures 1 and 2 below. When logs are hung on stratigraphic datums, as Figure 2 shows, geologic intervals are readily evident across many tens, if not hundreds or thousands of wells. Not only is the lateral consistency of strong events evident, such as the Codell in this case, but patterns of finer detail in the sequence stratigraphy (flooding surfaces, onlap, thickening and thinning from changing accommodation and sediment supply) become more visually apparent. Further refined picking of associated events is warranted but could prove tedious and time consuming if done manually.
ABSTRACT: Heterogeneity of an unconventional reservoir is one of the main factors affecting production. Well performance depends on the size and efficiency of the interconnected fracture “plumbing system”, as influenced by multistage hydraulic fracturing. A complex, interconnected natural fracture network can significantly increase the size of stimulated reservoir volume, provide additional surface area contact and enhance permeability. The purpose of this study was to characterize the natural fracture patterns occurring in the unconventional Niobrara reservoir and to determine the drivers that influenced fracture trends and distributions. Highly fractured areas/fracture swarm corridors were identified and integrated into a reservoir model though DFN (Discrete Fracture Network) application for further prediction of reservoir performance using reservoir simulations. The predictive capability of DFN models can aid in improved reservoir performance and hydrocarbon production through optimized well spacing, re-frac stage locations planning for existing wells as well as completion strategies design for new wells.
Summary The Codell Sandstone has recently been the subject of extensive exploration and subsequent development activity in both the Colorado and Wyoming portions of northern DJ Basin. The Niobrara Formation has been the primary historical exploration target since the late 1980's due to success at the Silo Field from horizontal wells drilled in the Niobrara B Bench. In 2009, EOG Resources discovered the Hereford Field with the Jake 02-01H, producing approximately 1700 barrels of oil per day initially from the Niobrara B Bench. The next two years in the area saw much drilling focused for the Niobrara B Bench with the completion of many non-commercial wells. In 2012, SM Energy drilled a lateral focused on evaluating the Codell Sandstone. Cirque Resources, Kaiser Francis and EOG soon followed with their own exploratory wells, establishing the play. This new play area is thermally in the oil window. Codell Sandstone oil producers have gas-oil ratios less than 2000 scf/bbl. The Codell Sandstone thins from north to south due to erosional truncation beneath an angular unconformity at the base of the Fort Hays Limestone Member of the Niobrara Formation. Gross thickness ranges from 18 to 33 feet. The Codell Sandstone is a very-fine to fine-grained sandstone and produces oil from two main facies: bioturbated sandstone and laminated sandstone. The laminated facies is parallel to sub-horizontally bedded, has 8 to 15 percent porosity, and .01 to 0.10 millidarcies permeability. The bioturbated sandstone has 8 to 13 percent porosity and .008 to .05 millidarcies permeability. The Codell Sandstone is a low-resistivity pay zone that produces oil with low water cuts from zones with less than 10 ohm-m resistivity. Clay content is 15–25% with abundant microporosity as imaged with epifluorescent microscopy, accounting for high bound water content and explaining the low formation resistivity. Oil typing indicates the oil found in the Codell is sourced from the Niobrara and is distributed across the area through migration. Oil saturation varies across the play depending the on the distance from areas of oil generation and expulsion into the Codell. Use of mercury capillary injection pressure analysis was essential in resolving the oil migration route throughout the play area. Drilling and completion techniques have evolved since the first wells were drilled. Best practices to date involve 1280 acre spacing units with 9300' lateral lengths, cemented liner with perf & plug completion techniques. Introduction The DJ Basin has been a very active province for exploration and development in the recent horizontal drilling boom since 2009. Driven primarily by the Niobrara Formation, the Codell Sandstone has also been a large contributor to activity. Due to all of this activity, both within the core of the Wattenberg Field as well as the step out activity in both Colorado and Wyoming, the production for the basin has increased from 192,000 BOEPD in 2010 to over 480,000 BOEPD in early 2016.
Summary ConocoPhillips built its position in the D-J Basin Niobrara play between 2010 and 2012 with current leasehold of approximately 130,000 net acres south east of Denver. Envisaged as a new play extension to Wattenberg Field, based on a thermal anomaly in Arapahoe County, early production expectations were based on the aggregate of Niobrara horizontal wells across the basin. Production results from early COP horizontal wells were difficult to compare with aggregate D-J basin production, and demanded a more granular approach to analogue selection. With the goal of identifying geologically comparable well groups, ConocoPhillips' Niobrara Exploration team assembled a database of 800+ horizontal wells and 1500+ vertical producers, paring down potential analogues by thermal maturity, API gravity, fractured reservoir, petrophysical properties, lateral length and completion type. Petrophysical parameters were mapped across the basin in > 3000 wells, and extrapolated to all horizontal producers to enable cross-plotting with production rates, EUR estimates from decline curve analysis and fluid properties. Sensitivity analysis revealed meaningful trends in well orientation, API gravity, proppant volumes, target horizon and the relevance of oil in place, which helps focus the appraisal program and identify critical uncertainties to test. Selecting analogue wells based on reservoir properties and comparable well design was critical to calibrate reservoir simulation models to better forecast production from horizontal wells in the area of interest.