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Something that struck Brian Price as odd when he started selling chemicals to shale producers a few years ago was how few of them were thinking about whether the fracturing additives they pumped might cause trouble downhole. The man who is now vice president of technology and strategic optimism at Rockwater Energy Solutions--yes, it is optimism--had spent years working offshore. Engineers working in the Gulf of Mexico worried about the possible impact of chemicals pumped into highly permeable sandstone reservoirs made up of minerals such as quartz and feldspar. Both are fairly inert compared to the highly reactive mix in shale formations. While the job of offshore teams is to methodically consider how to maximize production from a few high-cost wells that are expected to produce for decades, those in the shale business have used standard designs to mass-produce wells in bad-quality rock, with a goal of maximizing production in year one.
Unconventional completions engineering is often a game of inches. One where winning is increasingly defined by gaining incremental control over capital, geologic uncertainty, and preconceptions about how to do it right. This spirit of continuous improvement remained a chief undercurrent of this year's Unconventional Resources Technology Conference (URTeC) in Houston. Chevron and Occidental Petroleum (Oxy) were among the largest Permian Basin operators at the conference to reveal how their completions philosophies evolved amidst the onset of a low-capital environment. Chevron reports that it's saving around 8% on new well pads while also adopting new proppant schedules that have reduced its reliance on chemical additives.
During the 2021–2022 Distinguished Lecturer season, the following topics and speakers will be presented. A calendar of the lecturer schedule will be available at www.spe.org/dl/schedule. Are Traditional Laboratory Reservoir Fluid Characterizations Superior to Downhole In-Situ Digital Samples? Asphaltene Flow-Assurance Risks in Gas Injection: How are Pitfalls Brought Into the Open? To Increase Production, Listen to Your Well! Halliburton Production and Operations Machine Learning: Is it Magic or Hard Work?
Abstract A new, through-the-bit, ultra-slim wireline borehole-imaging tool for use in oil-based mud provides photorealistic images. The imager is designed to be conveyed through drill-pipe. At the desired well section, it exits the drill pipe through a portal drill bit and starts the logging. Field test measurements in several horizontal, unconventional wells in North America show images of fine detail with a large amount of geological information and high value for well development. A relatively new solution for conveying tools to the deepest point of a high angle or horizontal wells uses a drill bit with a portal hole at the bit face. As soon as the bit reaches the total depth, a string of logging tools is pumped down through the drill pipe. The tools exit the bit through the portal hole, arriving in the open hole and are ready for the up log. The tools operate on battery and store the log data in memory so that no cable is interfering as the drill pipe is tripped out of the well while the tools are acquiring data. The quality of wireline electrical borehole images in wells drilled with oil-based mud has significantly improved in recent years. Modern microresistivity imagers operate in the megahertz-frequency range, radiating the electromagnetic signal through the non-conductive mud column. A composite processing scheme produces high-resolution impedivity images. The new, ultra-slim borehole-imager tool uses these measurement principles and processing methods. Innovating beyond the existing tool designs the tool is now re-engineered to dimensions sufficiently slim to fit through drill pipes and to use through-the-bit logging techniques. The new, ultra-slim tool geometry proves highly reliable and, due to the deployment technique, highly effective in challenging hole conditions. The tool did not suffer any damage and showed only minute wear over more than twenty field test wells. The tool’s twelve-pad geometry provides 75% coverage in a six-inch diameter borehole and its image quality compares very well with existing larger tools. The field test of this borehole imaging tool covers all scenarios from vertical to deviated and to long-reach, horizontal wells. Geological structures, sedimentary heterogeneities, faults and fractures are imaged with detail matching benchmark wireline images. The interpretation answers allow operators of unconventional reservoirs to employ intelligent stimulation strategies based on geological reality and effective well development. A new high-frequency borehole imager for wells drilled with oil-based mud is introduced. Deployed through the drill pipe and its portal bit, the imager carries photorealistic microresistivity images into wells where conventional wireline conveyance techniques reach their limits in both practicality and viability.
Abstract Conventional resistivity models often overestimate water saturation in organic-rich mudrocks and require extensive calibration efforts. Conventional resistivity-porosity-saturation models assume brine in the formation as the only conductive component contributing to resistivity measurements. Enhanced resistivity models for shaly-sand analysis include clay concentration and clay-bound water as contributors to electrical conductivity. These shaly-sand models, however, consider the existing clay in the rock as dispersed, laminated, or structural, which does not reliably describe the distribution of clay network in organic-rich mudrocks. They also do not incorporate other conductive minerals and organic matter, which can significantly impact the resistivity measurements and lead to uncertainty in water saturation assessment. We recently introduced a method that quantitatively assimilates the type and spatial distribution of all conductive components to improve reserves evaluation in organic-rich mudrocks using electrical resistivity measurements. This paper aims to verify the reliability of the introduced method for the assessment of water/hydrocarbon saturation in the Wolfcamp formation of the Permian Basin. Our recently introduced resistivity model uses pore combination modeling to incorporate conductive (clay, pyrite, kerogen, brine) and non-conductive (grains, hydrocarbon) components in estimating effective resistivity. The inputs to the model are volumetric concentrations of minerals, the conductivity of rock components, and porosity obtained from laboratory measurements or interpretation of well logs. Geometric model parameters are also critical inputs to the model. To simultaneously estimate the geometric model parameters and water saturation, we develop two inversion algorithms (a) to estimate the geometric model parameters as inputs to the new resistivity model and (b) to estimate the water saturation. Rock type, pore structure, and spatial distribution of rock components affect geometric model parameters. Therefore, dividing the formation into reliable petrophysical zones is an essential step in this method. The geometric model parameters are determined for each rock type by minimizing the difference between the measured resistivity and the resistivity, estimated from Pore Combination Modeling. We applied the new rock physics model to two wells drilled in the Permian Basin. The depth interval of interest was located in the Wolfcamp formation. The rock-class-based inversion showed variation in geometric model parameters, which improved the assessment of water saturation. Results demonstrated that the new method improved water saturation estimates by 32.1% and 36.2% compared to Waxman-Smits and Archie's models, respectively, in the Wolfcamp formation. The most considerable improvement was observed in the Middle and Lower Wolfcamp formation, where the average clay concentration was relatively higher than the other zones. Results demonstrated that the proposed method was shown to improve the estimates of hydrocarbon reserves in the Permian Basin by 33%. The hydrocarbon reserves were underestimated by an average of 70000 bbl/acre when water saturation was quantified using Archie's model in the Permian Basin. It should be highlighted that the new method did not require any calibration effort to obtain model parameters for estimating water saturation. This method minimizes the need for extensive calibration efforts for the assessment of hydrocarbon/water saturation in organic-rich mudrocks. By minimizing the need for extensive calibration work, we can reduce the number of core samples acquired. This is the unique contribution of this rock-physics-based workflow.
Abstract Organic-rich mudrocks are complex in terms of rock fabric (i.e., the spatial distribution of rock components), which impacts electrical resistivity measurements and, therefore, estimates of hydrocarbon reserves. Conventional resistivity-saturation-porosity methods for assessment of water/hydrocarbon saturation do not reliably incorporate the spatial distribution of rock components and pores in the assessment of fluid saturation. Extensive calibration efforts are required for indirectly projecting the impact of rock fabric on resistivity models. For instance, none of the existing shaly-sand models incorporate a realistic distribution of clay network. This might be acceptable in conventional reservoirs. However, oversimplifying assumptions can cause significant uncertainty in reserves evaluation in organic-rich mudrocks. It should be noted that even the methods which incorporate the realistic distribution of rock components are difficult to calibrate. To address the aforementioned challenge, we introduce a joint interpretation of conventional resistivity and resistivity image logs to improve water saturation assessment by honoring the type of rock component, the spatial distribution of the conductive and non-conductive rock components, and the volumetric concentration of fluids and minerals in the rock. Borehole image logs are a source of high-resolution continuous rock sequence records and can provide detailed rock-fabric-related features. In this paper, we propose a method for the estimation of lamination density and mean resistivity value from image logs within each rock type. These fabric-related features are used to quantify the geometric model parameters for each conductive component of the rock. We use these geometric model parameters as inputs to a new resistivity model that considers volumetric concentration and spatial distribution of rock components for a depth-by-depth assessment of water saturation. The other inputs to the workflow are the volumetric concentration of conductive and non-conductive rock components, electrical conductivity of rock components, and porosity estimates from the joint interpretation of well logs. We successfully applied the proposed workflow to a dataset from the Wolfcamp formation in the Permian Basin in which resistivity image logs were available. We observed a measurable variation in estimated image-log-based geometric model parameters, which were in agreement with the visual content of the images. Incorporation of the estimated rock-class-based geometric model parameters in the resistivity model improved water saturation assessment. Results demonstrated a relative improvement in water saturation estimates of 44.2% and 59.1% against Waxman-Smits and Archie's models, respectively. We then used the estimated geometric model parameters for each rock type for a depth-by-depth assessment of water saturation in one additional well without image logs. This led to a faster and more reliable assessment of water saturation within a certain distance from the well with image logs, where the rock types remain comparable. This distance can be evaluated using variogram analysis. We demonstrated that using the estimated geometric model parameters could improve estimates of hydrocarbon reserves in the Permian Basin by approximately 34%. It should be noted that the proposed method for assessment of geometric model parameters is completely based on the actual spatial distribution of rock components and does not require core-based calibration efforts.
Johnson, Andrew C. (Schlumberger) | Miles, Jeffrey (Schlumberger) | Mosse, Laurent (Schlumberger) | Laronga, Robert (Schlumberger) | Lujan, Violeta (Schlumberger) | Aryal, Niranjan (Schlumberger) | Nwosu, Dozie (Schlumberger)
Abstract Formation water saturation is a critical target property for any comprehensive well log analysis program. Most techniques for computing saturation depend heavily on an analyst’s ability to accurately model resistivity measurements for the effects of formation water resistivity and rock texture. However, the pre-requisite knowledge of formation water properties, particularly salinity, is often either unknown, varying with depth or lateral extent, or is difficult to derive from traditional methods. A high degree of variability may be present due to fluid migration from production, water injection, or various geological mechanisms. In unconventional reservoirs, the complexity of the rocks and pore structure further complicates traditional interpretation of the available well logs. These factors introduce significant uncertainties in the computed fluid saturations and therefore can substantially affect final reserves estimates. A novel technique in geochemical spectroscopy has recently been introduced to distinguish the chlorine signals of the formation and borehole. The new, quantitative measurement of formation chlorine enables a direct calculation of bulk water volume for a given formation water salinity. When integrated into a multi-physics log analysis workflow, the chlorine-derived water volume can provide critical information on fluid saturations, hydrocarbon-in-place, and producibility indicators. This additional information is especially useful for characterizing challenging and complex unconventional reservoirs. We present the new technique through several full petrophysical evaluation case studies in organic shale formations across the U.S., including the Midland, Delaware, Marcellus, and DJ basins. We solve for formation-specific water salinity and bulk water volume through an optimization that combines chlorine concentration with resistivity and dielectric measurements. These outputs are integrated into comprehensive petrophysical evaluations, leveraging a suite of advanced well log measurements to compute final fluid and rock properties and volumetrics. The evaluations include geochemical mineralogy logs, 2D NMR analyses, dielectric dispersion analyses, basic log measurements, and multi-mineral models. The results underscore the utility of the new spectroscopy chlorine log to reduce petrophysical model uncertainties in an integrated workflow. While this workflow has been demonstrated here in several U.S. organic shale case studies, the fundamental challenges it addresses will make it a valuable solution for a range of unconventional reservoirs globally.
Nicholson, A. Kirby (Pressure Diagnostics Ltd.) | Bachman, Robert C. (Pressure Diagnostics Ltd.) | Scherz, R. Yvonne (Endeavor Energy Resources) | Hawkes, Robert V. (Cordax Evaluation Technologies Inc.)
Abstract Pressure and stage volume are the least expensive and most readily available data for diagnostic analysis of hydraulic fracturing operations. Case history data from the Midland Basin is used to demonstrate how high-quality, time-synchronized pressure measurements at a treatment and an offsetting shut-in producing well can provide the necessary input to calculate fracture geometries at both wells and estimate perforation cluster efficiency at the treatment well. No special wellbore monitoring equipment is required. In summary, the methods outlined in this paper quantifies fracture geometries as compared to the more general observations of Daneshy (2020) and Haustveit et al. (2020). Pressures collected in Diagnostic Fracture Injection Tests (DFITs), select toe-stage full-scale fracture treatments, and offset observation wells are used to demonstrate a simple workflow. The pressure data combined with Volume to First Response (Vfr) at the observation well is used to create a geometry model of fracture length, width, and height estimates at the treatment well as illustrated in Figure 1. The producing fracture length of the observation well is also determined. Pressure Transient Analysis (PTA) techniques, a Perkins-Kern-Nordgren (PKN) fracture propagation model and offset well Fracture Driven Interaction (FDI) pressures are used to quantify hydraulic fracture dimensions. The PTA-derived Farfield Fracture Extension Pressure, FFEP, concept was introduced in Nicholson et al. (2019) and is summarized in Appendix B of this paper. FFEP replaces Instantaneous Shut-In Pressure, ISIP, for use in net pressure calculations. FFEP is determined and utilized in both DFITs and full-scale fracture inter-stage fall-off data. The use of the Primary Pressure Derivative (PPD) to accurately identify FFEP simplifies and speeds up the analysis, allowing for real time treatment decisions. This new technique is called Rapid-PTA. Additionally, the plotted shape and gradient of the observation-well pressure response can identify whether FDI's are hydraulic or poroelastic before a fracture stage is completed and may be used to change stage volume on the fly. Figure 1: Fracture Geometry Model with FDI Pressure Matching Case studies are presented showing the full workflow required to generate the fracture geometry model. The component inputs for the model are presented including a toe-stage DFIT, inter-stage pressure fall-off, and the FDI pressure build-up. We discuss how to optimize these hydraulic fractures in hindsight (look-back) and what might have been done in real time during the completion operations given this workflow and field-ready advanced data-handling capability. Hydraulic fracturing operations can be optimized in real time using new Rapid-PTA techniques for high quality pressure data collected on treating and observation wells. This process opens the door for more advanced geometry modeling and for rapid design changes to save costs and improve well productivity and ultimate recovery.
Suarez-Rivera, Roberto (W. D. Von Gonten Laboratories) | Panse, Rohit (W. D. Von Gonten Laboratories) | Sovizi, Javad (Baker Hughes) | Dontsov, Egor (ResFrac Corporation) | LaReau, Heather (BP America Production Company, BPx Energy Inc.) | Suter, Kirke (BP America Production Company, BPx Energy Inc.) | Blose, Matthew (BP America Production Company, BPx Energy Inc.) | Hailu, Thomas (BP America Production Company, BPx Energy Inc.) | Koontz, Kyle (BP America Production Company, BPx Energy Inc.)
Abstract Predicting fracture behavior is important for well placement design and for optimizing multi-well development production. This requires the use of fracturing models that are calibrated to represent field measurements. However, because hydraulic fracture models include complex physics and uncertainties and have many variables defining these, the problem of calibrating modeling results with field responses is ill-posed. There are more model variables than can be changed than field observations to constrain these. It is always possible to find a calibrated model that reproduces the field data. However, the model is not unique and multiple matching solutions exist. The objective and scope of this work is to define a workflow for constraining these solutions and obtaining a more representative model for forecasting and optimization. We used field data from a multi-pad project in the Delaware play, with actual pump schedules, frac sequence, and time delays as used in the field, for all stages and all wells. We constructed a hydraulic fracturing model using high-confidence rock properties data and calibrated the model to field stimulation treatment data varying the two model variables with highest uncertainty: tectonic strain and average leak-off coefficient, while keeping all other model variables fixed. By reducing the number of adjusting model variables for calibration, we significantly lower the potential for over-fitting. Using an ultra-fast hydraulic fracturing simulator, we solved a global optimization problem to minimize the mismatch between the ISIPs and treatment pressures measured in the field and simulated by the model, for all the stages and all wells. This workflow helps us match the dominant ISIP trends in the field data and delivers higher confidence predictions in the regional stress. However, the uncertainty in the fracture geometry is still large. We also compared these results with traditional workflows that rely on selecting representative stages for calibration to field data. Results show that our workflow defines a better global optimum that best represents the behavior of all stages on all wells, and allows us to provide higher-confidence predictions of fracturing results for subsequent pads. We then used this higher confidence model to conduct sensitivity analysis for improving the well placement in subsequent pads and compared the results of the model predictions with the actual pad results.
Wu, Yinghui (Silixa LLC) | Hull, Robert (Silixa LLC) | Tucker, Andrew (Apache Corp.) | Rice, Craig (Apache Corp.) | Richter, Peter (Silixa LLC) | Wygal, Ben (Silixa LLC) | Farhadiroushan, Mahmoud (Silixa Ltd.) | Trujillo, Kirk (Silixa LLC) | Woerpel, Craig (Silixa LLC)
Abstract Distributed fiber-optic sensing (DFOS) has been utilized in unconventional reservoirs for hydraulic fracture efficiency diagnostics for many years. Downhole fiber cables can be permanently installed external to the casing to monitor and measure the uniformity and efficiency of individual clusters and stages during the completion in the near-field wellbore environment. Ideally, a second fiber or multiple fibers can be deployed in offset well(s) to monitor and characterize fracture geometries recorded by fracture-driven interactions or frac-hits in the far-field. Fracture opening and closing, stress shadow creation and relaxation, along with stage isolation can be clearly identified. Most importantly, fracture propagation from the near to far-field can be better understood and correlated. With our current technology, we can deploy cost effective retrievable fibers to record these far-field data. Our objective here is to highlight key data that can be gathered with multiple fibers in a carefully planned well-spacing study and to evaluate and understand the correspondence between far-field and near-field Distributed Acoustic Sensing (DAS) data. In this paper, we present a case study of three adjacent horizontal wells equipped with fiber in the Permian basin. We can correlate the near-field fluid allocation across a stage down to the cluster level to far-field fracture driven interactions (FDIs) with their frac-hit strain intensity. With multiple fibers we can evaluate fracture geometry, the propagation of the hydraulic fractures, changes in the deformation related to completion designs, fracture complexity characterization and then integrate the results with other data to better understand the geomechanical processes between wells. Novel frac-hit corridor (FHC) is introduced to evaluate stage isolation, azimuth, and frac-hit intensity (FHI), which is measured in far-field. Frac design can be evaluated with the correlation from near-field allocation to far-field FHC and FHI. By analyzing multiple treatment and monitor wells, the correspondence can be further calibrated and examined. We observe the far-field FHC and FHI are directly related to the activities of near-field clusters and stages. A leaking plug may directly result in FHC overlapping, gaps and variations in FHI, which also can be correlated to cluster uniformity. A near-far field correspondence can be established to evaluate FHC and FHI behaviors. By utilizing various completion designs and related measurements (e.g. Distributed Temperature Sensing (DTS), gauges, microseismic etc.), optimization can be performed to change the frac design based on far-field and near-field DFOS data based on the Decision Tree Method (DTM). In summary, hydraulic fracture propagation can be better characterized, measured, and understood by deploying multiple fibers across a lease. The correspondence between the far-field measured FHC and FHI can be utilized for completion evaluation and diagnostics. As the observed strain is directly measured, completion engineering and geoscience teams can confidently optimize their understanding of the fracture designs in real-time.