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Lab data on permeability, grain bulk modulus, drained bulk modulus, Skempton's pore pressure coefficient, and Biot's effective stress coefficient for Utah Forge Well 58-32 and Well 78-32. Work done as part of project number 5-2615 by the University of Oklahoma.
This is a presentation on the Development of a Smart Completion & Stimulation Solution project by Welltec in collaboration with the University of Oklahoma, presented by Yosafat Esquitin, a Senior Business Development Manager at Welltec. The project's objective was to develop an annular isolation system, a stimulation isolation system, and a multi-open-close flow system for geothermal environments. These systems were developed to enable effective zonal isolation and stimulation, implement downhole Enhanced Geothermal Systems (EGS) in any location, and extend the productive life of the geothermal well. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 7, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development EGS reservoirs and resources.
This is a presentation on the Application of Advanced Techniques for Determination of Reservoir-Scale Stress State at Utah FORGE project by the University of Oklahoma, presented by Dr. Ahmad Ghassemi, McCasland Chair Professor. The project's objective was to develop a methodology for the determination of reservoir-scale in-situ stress and use it to estimate the stress state at Utah FORGE. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 7, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.
This is a presentation on the Experimental Determination and Modeling-Informed Analysis of Thermo-poromechanical Response of Fractured Rock for Application to Utah FORGE project by the University of Oklahoma, presented by Dr. Ahmad Ghassemi, McCasland Chair Prof. The project objective is to improve understanding and control of coupled thermo-poromechanical (or thermo-hydro-mechanical- TPM) processes in reservoir development, and to study any role in interpretations of the fracture closure. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 8, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.
This is a presentation on the Design and Implementation of a Novel Multi-Frac Stimulation Concept by The University of Oklahoma, presented by Ahmad Ghassemi. This slide presentation video discusses the design and implementation of a reservoir stimulation concept improving near-wellbore and well-to-well conductivity while enhancing the SRV and promoting self-propping and heat exchange. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 13-15, 2024.
Multidimensional, experimental and modeling evaluation of permeability evolution, the Caney Shale Field Lab, OK, USA
Caney shale is one of the emerging oil reservoirs in Oklahoma. Understanding the impact of effective stress on its mechanical properties is critical for predicting hydraulic fracture geometry and overall hydrocarbon production. The objective of our study is to evaluate the impact of effective stress on the dynamic Young’s modulus using ultrasonic velocity measurements for Caney shale samples. A triaxial cell was utilized to measure ultrasonic (P-wave and S-wave) velocities for ten downhole Caney shale samples under various effective stresses to indirectly assess the impact of pore pressure change. The dynamic Young’s moduli estimated from these measurements were integrated with available conventional well logs (excluding sonic logs) and triaxial test results from Benge et al. (2021) to predict the static Young’s modulus using Random Forest (RF) and Extreme Gradient Boosting (XGBoost) models. The results showed that the estimated dynamic Young’s moduli from ultrasonic measurements were higher than the corresponding static Young’s modulus of cores from the same vertical well at similar depths. With increasing effective stress, the dynamic Young’s modulus increased for all samples. The estimated dynamic-to-static correction factor tended to be higher in zones of high neutron porosity (PHIN) and low density compared to other zones. Finally, SHapley Additive exPlanations (SHAP) for RF and XGBoost models identified depth, gamma ray (GR), and PHIN as key features for predicting the static Young’s modulus. This study enhances our understanding of the dynamic and static Young’s moduli for the Caney shale interval, as a function of effective stress and conventional well logs. The findings from this study can improve predictions of production throughout the well's lifespan by offering insights into the mechanical property degradation resulting from pore pressure depletion.
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-A74 ARM SGP milo field. This is the FLUXNET version of the carbon flux data for the site US-A74 ARM SGP milo field produced by applying the standard ONEFlux (1F) software. Site Description - This site is located near the ARM SGP Central Facility at the intersection of Oklahoma highways 11 and 74, 16.5 km East of Medford, OK
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-AR1 ARM USDA UNL OSU Woodward Switchgrass 1. This is the FLUXNET version of the carbon flux data for the site US-AR1 ARM USDA UNL OSU Woodward Switchgrass 1 produced by applying the standard ONEFlux (1F) software. Site Description - The ARM USDA UNL OSU Woodward Switchgrass 1 tower is located on public land owned by the USDA-ARS Southern Plains Range Research Station in Woodward, Oklahoma. The site is on a former native prairie that is in the process of changing to switchgrass. A second companion site (ARM USDA UNL OSU Woodward Switchgrass 2) is on a former wheat field. In Spring 2009, the former native prairie site was burned, cattle were put on the pasture to graze down emergent grass, and broadleaf herbicide was sprayed. In Summer 2009, the cattle were removed from the pasture, and the site was sprayed with herbicide to kill all grass. In Spring 2010, prior to the planting of switchgrass, final herbicide was sprayed to kill cheat grass and to control broadleaf plants.
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-AR2 ARM USDA UNL OSU Woodward Switchgrass 2. This is the FLUXNET version of the carbon flux data for the site US-AR2 ARM USDA UNL OSU Woodward Switchgrass 2 produced by applying the standard ONEFlux (1F) software. Site Description - The ARM USDA UNL OSU Woodward Switchgrass 2 tower is located on public land owned by the USDA-ARS Southern Plains Range Research Station in Woodward, Oklahoma. The site is on a former wheat field that is in the process of changing to switchgrass. A companion site (ARM USDA UNL OSU Woodward Switchgrass 1) is on a former native prairie. Previous wheat was planted in Fall 2008. In Spring 2009, herbicide was applied to kill the wheat prior to switchgrass planting. Later in the year, the site was sprayed with post-emergence herbicide. In 2010, fertilization occurred before herbicide was sprayed for broadleaf control.
This is the AmeriFlux version of the carbon flux data for the site US-A37 ARM-SGP-Waukomis. Site Description - The E37 site is located in the middle of a grassy field with a cultivated field to the South, near Waukomis, Oklahoma.
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-A37 ARM-SGP-Waukomis. This is the FLUXNET version of the carbon flux data for the site US-A37 ARM-SGP-Waukomis produced by applying the standard ONEFlux (1F) software. Site Description - The E37 site is located in the middle of a grassy field with a cultivated field to the South, near Waukomis, Oklahoma.
As the carbon sequestration community prepares to scale up the number and size of commercial operations, the need for tools and methods to assess and mitigate risks associated with these operations becomes increasingly important. One outstanding question is whether aftershocks of induced events decay quickly after injection operations cease or if aftershock activity persists for hundreds of years before returning to background levels more akin to tectonic events (Stein and Liu, 2009). Appropriate estimates of the aftershock duration impact several operational management decisions including mitigation strategies and post-injection monitoring for seismic activity. It is hypothesized that induced earthquake rates may diminish more quickly after injection is stopped, owing to higher stressing rates from injected fluids. Alternatively, it is plausible that only the first event in the sequence is induced by increased fluid overpressures, whereas subsequent events (e.g., aftershocks) respond to the stored tectonic stresses and static and dynamic stress changes due to the mainshock (Keranen et al., 2013). Further, if the aftershock duration can be linked to stressing rates due to injection, then it follows that operational strategies to reduce seismic hazard by reducing injection rates or volumes may be successful. However, if aftershocks of induced events are relieving stored tectonic stresses, then altering injection volumes may not alleviate ongoing seismic activity. Furthermore, knowledge of an aftershock duration could aid in the determination of an appropriate post-injection monitoring period for ongoing seismicity, which is a factor in overall operational costs. In this study, we model induced seismicity sequences in Oklahoma with a coupled Coulomb rate–state earthquake rate model (Dieterich, 1994; Kroll et al., 2017) to estimate aftershocks durations. Results for the current study indicate that elevated rates of aftershock activity following induced mainshocks return to background seismicity rates in less than five years, contrary to the tens to hundreds of years observed for tectonic aftershocks.
Abstract Seismicity in southern Kansas and northern Oklahoma in the past decade has been associated with fluid injections. In southcentral Kansas, the Wellington earthquake catalog is primarily composed of local, low-magnitude events. Approximately 22% of recorded earthquakes over a 2.5 yr period exhibit a seismic phase arriving between the direct P phase and direct S phase with particle motion similar to the P wave. This intermediate phase was identified as an S to P conversion (SP phase) occurring in the sedimentary rocks instead of the hypothesized basement to sedimentary section transition. We exploit the SP-converted phases to improve the depth accuracy of shallow earthquakes and to constrain VP/VS. The revised depth calculations further confirm that these local induced earthquakes are occurring in the shallow crystalline basement, below the sedimentary section in which fluids are injected.
Wastewater disposal is primarily responsible for the increased seismicity rate since ~2013 in southern Kansas. Previous work that used shear-wave splitting (SWS) in southern Kansas interpreted an ~90° temporal rotation in the fast polarization direction and attributed it to increased pore pressures resulting from fluid injection. However, this interpreted rotation coincided with a change in the stations used to make the SWS measurements. We investigate the temporal variability of fast azimuths in southern Kansas by making SWS measurements on earthquake families with similar source–receiver paths recorded on a stable local seismic network. We select high-quality SWS measurements by investigating the stability of results across 65 different frequency bands between 0.5 and 15 Hz. We find that the fast polarization direction in southern Kansas is relatively constant with an average east-northeast (~N79°E) orientation between 2014 and 2017. Our fast polarization measurements are primarily a reflection of the maximum principal horizontal stress direction (SHmax). We observe a slight spatial change in SHmax to the northeast (~N55°E) near the Nemaha ridge in Oklahoma. However, we do not observe any significant temporal rotation of SHmax or variation in delay time (i.e., crack density) in southern Kansas, contrary to the earlier study. The previously interpreted ~90° rotation may either be a reflection of a very local stress change or a misinterpretation of SWS results potentially due to the use of inconsistent source–receiver paths. Our SWS measurements cover the period of peak wastewater disposal and seismicity rates and suggest an absence of significant temporal rotations in the local anisotropy and stress orientations associated with wastewater disposal.
The association of phase picks to form events is one of the fundamental components of seismology. Large and dense sensor networks, such as >1000 geophone arrays (and distributed acoustic sensing), offer unique challenges in association due to the vast numbers of observations and high likelihood of errant picks. In addition, the large number of stations can greatly increase the time it takes to perform the association. For this reason, machine learning (ML) methods might provide a more optimal method of association for such networks. In this work, we examine how well ML methods (e.g., Gaussian mixture model association, PhaseLink, and Graph Earthquake Neural Interpretation Engine) can incorporate dense seismic arrays into regional networks and how well they handle the increasing numbers of stations. Here, we test their capabilities on two dense seismic deployments, one within Rock Valley Nevada (52 nodes and a 9-station sparse local network), and the LArge-n Seismic Survey in Oklahoma dense nodal array (>1800 vertical-component geophones). Processing data from these two different styles of dense seismic deployments allows testing of how the ML algorithms can merge array data with a broader regional network, how they deal with poorly picked phases, and how they handle anthropogenic noise. We compare the ML-associated bulletins to those obtained using the Rapid Earthquake Association and Location algorithm, a more traditional method of association. We find that there are very small differences in results between the methods for small networks (<100 stations) with low pick rates. For large networks (>1000), there are enough errant picks that some of the ML methods start to create false events out of noise. We also find that the ML methods vary in computation time significantly but are all faster than the traditional method tested here.
This document describes the algorithm used for the Surface Cloud Grid Value-Added Product (VAP). This VAP uses as input the 15-min. output from the Shortwave (SW) Flux Analysis VAP (see Long 2001; Long and Ackerman 2000; Long et al. 1999) from the Atmospheric Radiation Measurement (ARM) Climate Reseach Facility (ACRF) Southern Great Plains (SGP) Central Facility and extended facilities. This network of 21 sites is unevenly spaced over northern Oklahoma into southern Kansas, covering an area from 95.5° to 99.5° west longitude and 34.5° to 38.5° north latitude. For research applications such as single-column modeling, an estimate of the cloud and cloud effects distribution over this entire domain is desirable. The Surface Cloud Grid VAP applies a multi-pass weighted sum analytic approximation technique (Caracena 1987), which uses Gaussian weighting and an imposed scale length, to interpolate to a 0.25° by 0.25° lat/long grid over the SGP domain. The output, like the input, includes solar elevation angles of 10° or greater.
This study estimates the cost of saving a therm of natural gas from energy efficiency programs funded by utility customers during the period 2012 to 2017. Berkeley Lab researchers compiled and analyzed efficiency program data reported by investor-owned utilities and other program administrators in a dozen states representative of the four U.S. Census regions — Arkansas, California, Connecticut, Iowa, Massachusetts, Michigan, Minnesota, New Jersey, New York, Oklahoma, Rhode Island and Utah. Depending on the year, the dataset accounts for about 50 percent to 70 percent of annual national spending on natural gas efficiency programs. The estimated cost of saving natural gas during the study period is $0.40 per therm. The analysis also includes estimates of the program administrator cost of saved energy for three core sectors for natural gas: commercial and industrial, residential, and low-income households. It aggregates these sectors to provide regional and national values. Our metrics include savings-weighted averages, unweighted medians, and interquartile ranges (25th and 75th percentiles) of the levelized program administrator cost of saving gas, in constant 2017 dollars. In addition, the study analyzes cost trends during the study period, finding that average program costs trended downward. The U.S. Department of Energy’s Building Technologies Office supported this work.