The Powder River Basin has emerged over the past year as the latest source of oil production growth for the Lower 48. Companies ranging from a reborn Samson Resources to US onshore mainstays Devon, Chesapeake, and EOG are now betting on the basin to become a long-term core asset. Colorado’s industry lacks the size, variety, and Wild West characteristics of Texas, but that is precisely why the Centennial State’s oil production is surging to record levels. This paper describes a comprehensive field study of eight horizontal wells deployed in the stacked Niobrara and Codell reservoirs in the Wattenberg Field (Denver-Julesburg Basin).
The large independent put together a team of data scientists, software developers, and petrotechnical staff to create a forward-looking vision for how to use digital technology to solve problems. Baker Hughes is still a GE company, but it has partnered with a second company for artificial intelligence expertise, C3.ai. The deal is expected to speed the integration of AI into oilfield operations by the company which also markets GE’s device analytics platform, Predix. Marathon Oil says its shale fields are producing more oil and gas with less hands-on work from company personnel thanks to a growing arsenal of digital technologies and workflows. Malaysia’s Petronas, Shell Malaysia, and Thailand’s PTTEP are now in the midst of full-scale digital adoption.
Travers, Patrick (Dolan Integration Group) | Burke, Ben (HighPoint Resources) | Rowe, Aryn (HighPoint Resources) | Hodgetts, Stephen (Dolan Integration Group) | Dolan, Michael (Dolan Integration Group)
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 (1H and 2H) and oxygen (16O and 18O) 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 2H and 18O. 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.
The Niobrara interval in the Denver-Julesberg (DJ) Basin contains several important unconventional hydrocarbon targets. However, the Niobrara is extensively faulted, which poses challenges for accurately landing and steering laterals in zone. Insight into small faulted structures in the Niobrara using traditional manual fault interpretation techniques is challenging because of the tuning thickness in seismic data. Fault throws less than the tuning thickness are difficult to interpret and incorporate into geosteering plans. Consequently, drillers frequently find themselves out of zone after crossing these small faults. Using independent information about fault locations and throws provided from multiple horizontal wells in the DJ Basin, this paper demonstrates the fault likelihood attribute (Hale, 2013) can resolve fault throws as small as 10 ft, allowing seismic-based well plans and unconventional project economics to be significantly improved.
Traditional geoscience data interpretation workflows in support of well planning can be tedious and time consuming, requiring manual fault picking on seismic profiles in conjunction with horizon tracing and gridding for structural mapping. The emergence of unconventional resource plays requires both more efficient geoscience workflows to support round-the-clock drilling operations and more detailed structural interpretations to help ensure laterals are steered along sweet spots. Pre-drill mapping of small-scale faults is therefore of particular importance for safe operations and helping ensure that lateral wells stay in zone.
Recent advances in fault-sensitive post-stack seismic attributes are changing the way subsurface professionals think about faults and how to map them in 3D space. In particular, the fault likelihood attribute (Hale, 2013) has provided a breakthrough improvement in the quality of seismic-derived fault attributes. Typically, the fault likelihood attribute is used in exploration settings to rapidly generate a broad-scale structural interpretation, being used both as a guide to manual fault interpretation and as input into automated fault extraction algorithms. This paper demonstrates the value of fault likelihood in development settings for assisting the well planning and geosteering process.
Seismic attributes can be both powerful and challenging to incorporate into interpretation and analysis. Recent developments with machine learning have added new capabilities to multi-attribute seismic analysis. In 2018, Geophysical Insights conducted a proof of concept on 100 square miles of multi-client 3D data jointly owned by Geophysical Pursuit, Inc. (GPI) and Fairfield Geotechnologies (FFG) in the Denver-Julesburg Basin (DJ). The purpose of the study was to evaluate the effectiveness of a machine learning workflow to improve resolution within the reservoir intervals of the Niobrara and Codell formations, the primary targets for development in this portion of the basin.
The seismic data are from Phase 5 of the GPI/Fairfield Niobrara program in northern Colorado. A preliminary workflow which included synthetics, horizon picking and correlation of 28 wells was completed. The seismic volume was re-sampled from 2 ms to 1 ms. Detailed well time-depth charts were created for the Top Niobrara, Niobrara A, B and C benches, Fort Hays and Codell intervals. The interpretations, along with the seismic volume, were loaded into the Paradise® machine learning application, and two suites of attributes were generated, instantaneous and geometric. The first step in the machine learning workflow is Principal Component Analysis (PCA). PCA is a method of identifying attributes that have the greatest contribution to the data and that quantifies the relative contribution of each. PCA aids in the selection of which attributes are appropriate to use in a Self-Organizing Map (SOM). In this case, 15 instantaneous attribute volumes, plus the parent amplitude volume, were used in the PCA and eight were selected to use in SOMs. The SOM is a neural network-based machine learning process that is applied to multiple attribute volumes simultaneously. The SOM produces a non-linear classification of the data in a designated time or depth window.
For this study, a 60-ms interval that encompasses the Niobrara and Codell formations was evaluated using several SOM topologies. One of the main drilling targets, the B chalk, is approximately 30 feet thick; making horizontal well planning and execution a challenge for operators. An 8 X 8 SOM applied to 1 ms seismic data improves the stratigraphic resolution of the B bench. The neuron classification also images small but significant structural variations within the chalk bench. These variations correlate visually with the geometric curvature attributes. This improved resolution allows for precise well planning for horizontals within the bench. The 25 foot thick C bench and the 17 to 25 foot thick Codell are also seismically resolved via SOM analysis. Petrophysical analyses from wireline logs run in seven wells within the survey by Digital Formation; together with additional results from SOMs show the capability to differentiate a high TOC upper unit within the A marl which presents an additional exploration target. Utilizing 2d color maps and geobodies extracted from the SOMs combined with petrophysical results allows calculation of reserves for the individual reservoir units as well as the recently identified high TOC target within the A marl.
The results show that a multi-attribute machine learning workflow improves the seismic resolution within the Niobrara reservoirs of the DJ Basin and results can be utilized in both exploration and development.
Well-to-well interference is an increasingly discussed issue. Previously drilled and producing “parent” wells and recently drilled “child” wells are yielding a reduction in recovery rates in both short and long-term cases due to interference. A primary contributor to the variability in production is the presence of pressure sinks as the result of production depletion in the parent wells. Infill drilling will continue to occur in the development of unconventional plays, and it is crucial to gain an understanding of the impacts of well-to-well interference on hydraulic fracture generation.
This paper discusses a detailed approach to investigating well-to-well interference based on integrating hydraulic fracture modeling and reservoir simulation in two different formations, the Niobrara and Codell, in the Denver-Julesburg Basin. The geomechanical properties were calibrated by DFIT data and pressure matching of the parent well treatments. The resulting parent well fracture geometries were incorporated into a numerical reservoir model to determine the pressure depletion envelopes. The imported depletion model allows for the simulation of the child well treatments and associated impacts of the pressure sinks on fracture generation and the interaction between child and parent wells. The resulting depletion model provided a framework to investigate various methods to mitigate the effects of well-to-well communication in subsequent development. The developed workflow of well-to-well interference is applicable in understanding the effects of infill development in other producing basins.
The modeled child well treatments resulted in a clear indication of well-to-well communication with the parent wells that was attributable to pressure depletion. Actual field bottom-hole pressure measurements validated these results in the parent wells captured during the time of the child well treatments. Resulting proppant concentrations of the child well fractures indicated that the majority of the proppant transports towards the parent wells. Very little effective conductivity exists in the opposing direction of the depleted regions.
Slickwater treatment simulations indicate extremely asymmetric fractures that stay isolated to their respective target bench. For child wells in the same bench as the parent wells, fractures propagate directly toward the parent wells, with little to no fracture growth in the opposite direction.
Protection frac simulations indicate beneficial or detrimental results depending on the amount of repressurization that is achieved and the distance that the pressure transient extends into the reservoir. Re-pressurizing the reservoir surrounding the parent wells by 1,000 psi resulted in a reduction of well interference. A 500-psi scenario resulted in increased well interference between the parent wells. Several wells communicated with both parent wells due to the repressurization being insufficient to offset the depletion.
Natural repressurization of the reservoir to mitigate the effect of well interference was also investigated by using the reservoir model. Simulation of the parent wells being shut-in for three months prior to the child well treatments resulted in a pore pressure increase of only 280 psi. Based on the protection frac sensitivity of 500 psi, this is not a large enough repressurization to mitigate well-to-well interference successfully in the modeled scenarios.
The ultimate oil recovery from liquid-rich unconventional reservoirs is less than ten percent, thus a great interest in developing improved oil recovery (IOR) methods that can increase oil production from such reservoirs economically. Classical waterflooding in unconventional reservoirs is not plausible because of the small pore sizes and low permeability of shale reservoirs. However, when low salinity water enters the stimulated reservoir macrofractures via the hydraulic fracture stages in shale reservoirs, an osmotic pressure gradient forms because of the salinity contrast. Even in oil-wet shale reservoirs, such osmotic pressures prevail leading to brine imbibition into the matrix and generating counter-current flow of oil into the fractures. In this paper, we present a new method to measure the osmotic pressure in core samples. The method was applied to cores from Niobrara and Codell formations in the DJ basin. The osmotic pressure leads to enhanced oil recovery (EOR) in laboratory cores and could impact EOR in shale reservoirs.
Osmotic pressures, measured in low permeability shale cores, plus a precise thermodynamic calculation of the activity coefficients enabled us to calculate the ‘membrane efficiency’ of the cores. We used a high-speed centrifuge, first to saturate the cores with formation brine; second, we injected oil into the core to displace brine (1st drainage cycle); third, we allowed spontaneous imbibition of brine into the core; fourth, we conducted force imbibition displacement of the oil with brine until core reaches residual oil saturation. Because osmotic pressure is the difference between the high-salinity and low-salinity capillary pressures, the experimental process was repeated using low-salinity brine. Furthermore, we determined improved oil recovery (IOR) fraction which is the incremental oil recovered during low-salinity experiments and is a measure of IOR.
In this paper, we present a novel technique using high-speed centrifuge to measure osmotic pressure rapidly. The measured osmotic pressure of Codell sandstone, with permeability of 0.0085-0.0105 mD, was 2.4 % of the calculated perfect membrane osmotic pressure. Similarly, the measured osmotic pressure of Niobrara B-chalk, with permeability of 0.0022-0.0099 mD, was 74.9 % of perfect membrane osmotic pressure. When we account for the chalk solubility in brine, the calculated osmotic pressure is about 50% of that of the perfect membrane. Finally, the oil produced via osmotic pressure in oil-wet cores can be considered a potential method to enhance oil recovery in liquid-rich shale reservoirs.
Quantitative structural geology techniques can be used in conjunction with seismic data to define fault locations and geometry to reduce risk when planning horizontal wells. Unconventional plays in the past decade focus on basins characterized by largely horizontal stratigraphy and minimal faulting. However, even basins with minimal structure contain small-scale faults that pose unique risks to horizontal drilling. A fault with 100’ of throw or less can present well-bore stability issues due to natural fracturing and rock strength contrasts across faults. Seismic data can image these faults but because of their subdued nature, reliably interpreting their geometry and understanding the associated drilling risks can be difficult.
We present case studies examining seismic sections from the Denver basin where horizontal wells intercept small-scale normal faults. These faults are visible on the seismic sections where they cut across the Niobrara at 30 – 45°. Wells that pass above, below, or intersect the faults at high angles are generally drilled and completed without issue. At deeper levels, wells intersected the same faults at very low angles (where fault dips < 30°) and experienced drilling and completion issues. The transition from steep fault dips within the Niobrara to low fault dips at deeper levels is not well resolved in the seismic sections but clearly represents a drilling hazard that should be considered.
The geometry of the faults can be estimated using structural forward modeling and area-depth-strain (ADS) analysis. These established structural geology methods quantitatively relate seismically-imaged fold shape and horizon displacements to the underlying fault geometry. We use these methods to compute the deep fault geometry from the seismically observed folding of the Niobrara formation. We demonstrate that the wellbore collapse was related to fault angle and for a shorter lateral distance. This strongly suggests that the listric bends in these faults is a high-risk zone.
Objectives - Image-Based Rock Physics (IBRP) simulation of petrophysical properties based on sub-micron to micron-scale images of very fine-grain rocks is constrained by the resolution and range of various imaging techniques used. Unlike some conventional sandstone and carbonate reservoir rock where a single Micro-Computed X-ray Tomography (μCT) volume images nearly all of the significant pores and pore throats, many low-permeability rock types contain phase regions with micro-pores and pore throats, including intergranular microcrack pores, that are not accurately resolved at the required μCT scale needed for a representative elementary volume (REV) for the whole rock. Properties for these regions are obtained at a finer-scale or using a different measurement method and these properties then assigned to the phase regions at the larger REV scale. This study explores the methodology involved in obtaining and assigning microcrack properties in μCT rock images and demonstrates a workflow to handle uncertainty in the location and properties of microcracks using two representative low-permeability sandstones.
Methods/Procedures/Process - The workflow combines μCT images of a mini-plug sample (~50mm3), which represents the rock REV, with Focused Ion Beam - Scanning Electron Microscopy (FIB-SEM) images (~200μm3) of regions of various types of observed microporosity (including intergranular microcrack pores) which occur within the REV sample. Different representative types of microporosity regions were imaged and properties calculated from the higher-resolution FIB-SEM image volumes. For some fraction of μCT microporosity regions, such as micro-fractures, their locations in the REV μCT sample was known but the micro-fracture properties were not known. A sub-resolution micro-fracture model was numerically constructed, honoring the mineral facies morphology and microporosity types assigned based on their respective distributions as observed in high resolution SEM images. Resultant porosity, capillary pressure and flow properties on the larger REV volume were cross-validated with independent core analysis measurements.
Results/Observations/Conclusions - This study illustrates a workflow for assigning properties, obtained at finer scales or using other measurement methods, to regions in the REV at larger scale but lower resolution. The resulting rock model produces the same porosity, permeability, and capillary pressure as core analysis measurements, and has the potential to predict relative permeability.
Applications/Significance/Novelty - It is expected that the majority of low-permeability rocks require an upscaling methodology similar to that developed in this study for IBRP computations and integration with core analysis. Using this methodology IBRP offers deeper understanding of building blocks of the upscaled-properties measured by core analysis. IBRP also offers the ability to measure/compute relative permeabilities that are nearly physically impossible to measure on core and the ability to construct digital rocks that allow evaluation of complete suites of rocks and their properties.
This paper was prepared for presentation at the Unconventional Resources Technology Conference held in Denver, Colorado, USA, 22-24 July 2019. The URTeC Technical Program Committee accepted this presentation on the basis of information contained in an abstract submitted by the author(s). The contents of this paper have not been reviewed by URTeC and URTeC does not warrant the accuracy, reliability, or timeliness of any information herein. All information is the responsibility of, and, is subject to corrections by the author(s). Any person or entity that relies on any information obtained from this paper does so at their own risk. The information herein does not necessarily reflect any position of URTeC. Any reproduction, distribution, or storage of any part of this paper by anyone other than the author without the written consent of URTeC is prohibited.