Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “DRILLING”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Modeling of heat extraction from variably fractured porous media in Enhanced Geothermal Systems

Modeling of heat extraction in Enhanced Geothermal Systems is presented. The study builds on recent studies on the use of directional wells to improve heat transfer between doublet injection and production wells. The current study focuses on the influence of fracture orientation on production temperature in deep low permeability geothermal systems, and the effects of directional drilling and separation distance between boreholes on heat extraction. The modeling results indicate that fracture orientation with respect to the well-pair plane has significant influence on reservoir thermal drawdown. As a result, the vertical well doublet is impacted significantly more than the horizontal well doublet

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Conceptual model of the Tatun geothermal system, Taiwan

Here, the Tatun geothermal system, located in northern Taiwan, is hosted by the Plio-Pleistocene Tatun volcanic group, consisting dominantly of andesitic lavas, domes and pyroclastic flows. During the late 1960s and early 1970s, geologic mapping, geochemical sampling, geophysical surveys, and the drilling of numerous exploration and temperature gradient wells were conducted at Tatun under the leadership of the Mineral Research and Service Organization (MRSO), the predecessor to the geothermal group at the Industrial Technology Research Institute (ITRI). Deep (1–2 km) wells encountered commercial temperatures (200–300 °C) in the Matsao area, but these initial exploration efforts were discouraged by the presence of very acidic (pH < 3.5) and highly corrosive fluids. Numerous geoscience studies conducted over the past 15 years at Tatun have shown that the central portion of the system is dominated by corrosive volcanic fluids, as evidenced by abundant SO 2 as well as HCl. More reduced gases are encountered on the flanks of the system, suggesting that water-rock interaction may have at least partly neutralized the volcanic-derived fluids on the margins of this geothermal system.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Characterization of laboratory-scale hydraulic fracturing for EGS

To investigate the impact of reservoir stimulation by hydraulic fracturing, a series of advanced lab-scale block tests were conducted with multiple measurement methods to characterize the fracture and to assess the operation and the performance of an enhanced or engineered geothermal system (EGS). The stimulation test samples were 330-mm cubic blocks of Sierra White granite with one injection well and four producers drilled into it. Acoustic emissions generated during the fracture initiation and propagation were monitored with twenty AE sensors mounted on all sides of the block to help characterize the fracture initiation and propagation process. The recorded AE signals were analyzed to obtain the event location and the failure mechanism. The localized AE events shows that due to the low viscosity of the fracturing fluid (water), the fracture propagated rapidly and took only about 1.4 s to reach near the block surface. During the fracturing phase, about 47 percent of the events were determined to be shear/mixed mode failure events, 28 percent tensile failure events, and 25 percent compressional failure events. Just after the simulation, a step-rate (constant flowrate) injection test was carried out to investigate the reservoir injectivity enhancement. During this phase additional compressional failure events were observed and the percentages of tensile failure and shear/mixed mode failure decreased. The dramatic increase of the injection rate with small increments of the injection pressure demonstrates the nonlinear response of the fracture to effective normal stress variation with much higher fracture opening increase during the low effective normal stress interval. Hydraulic fracturing tests under different stress levels show that more AE hits/events are recorded when the rock block is under higher applied stress. The reconstructed 3D fracture geometry shows good agreement with the AE monitoring results. After fracturing, a tracer test was carried out and the fracture aperture was estimated to be around 139 μm. The tracer recovery curve shows two linear portions of the tracer tail on a semi-log plot similar to that observed in some field data and predicted by numerical modeling. Laser scanning of the fracture surfaces indicates that the induced fracture has a rough surface with a joint roughness coefficient (JRC) of 12.98 and tortuosity of 1.10, both of which are slightly larger than that from the Brazilian test fracture on the same rock. The thin section and SEM observations show that the fracture follows the weak boundaries between the Quartz and Albite grains or the weak beddings in the grains.

58 GEOSCIENCES↗
DOE OSTI2020

Play Fairway analysis of geothermal resources across the State of Hawai‘i: 4. Updates with new groundwater chemistry, subsurface stress analysis, and focused geophysical surveys

This paper is the fourth in a series on a play fairway analysis of geothermal resources across the State of Hawai‘i. Here we describe recent exploration activities that include groundwater sampling in ten locations statewide, as well as geophysical surveys on Lana‘i, across the SW rift of Haleakala Volcano (Maui), and surrounding Mauna Kea Volcano (Hawai‘i Island). We derive a first-order method for computing topographic stress using Green’s functions, finding that topography can induce appreciable crustal stress. We develop a new method for incorporating depth information about resistivity, density, and topographic stresses into our previously published equations to calculate resource probability and confidence. We incorporate newly collected and modeled data into our calculations to update statewide maps of probability and confidence. Lana‘i Island and southeast Mauna Kea are identified as the top targets for exploratory drilling. The east rift of Haleakala Volcano, the southern-most region of Mauna Loa’s SW rift (Hawai‘i Island), and central Kauai are identified as targets for geophysical surveying.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis

Play fairway analysis (PFA) is commonly used to generate geothermal potential maps and guide exploration studies, with a particular focus on locating and characterizing blind geothermal systems. This study evaluates the application of machine learning techniques to PFA in the Great Basin region of Nevada. Following the evaluation of various techniques, we identified two approaches to PFA that produced promising results, 1) supervised Bayesian probabilistic neural networks to generate geothermal potential maps with confidence intervals, and 2) unsupervised principal component analysis paired with k-means clustering to generate both cluster maps to help identify spatial patterns, as well as new combined feature inputs. We applied these techniques to perform a comparative analysis between two principal sets of geological and geophysical features related to permeability and heat and a set of positive (known geothermal resources) and negative training sites (known drill sites with unsuitable geothermal conditions). We found that these methods constrain previously unrecognized feature controls on geothermal favorability, many of which are spatially organized within the extent of cluster groups and the major structural-hydrologic domains of the study area. Furthermore, we utilized exploratory unsupervised modeling to highlight spatial relationships between input data and predictive output results of our supervised modeling. As a result, we demonstrate how our models compare to the previous Nevada PFA and how the rapid insights these machine learning techniques offer may support future assessments of both known and undiscovered blind geothermal systems in the Great Basin region of Nevada and beyond.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Geothermal Play Fairway Analysis, Part 2: GIS methodology

Play Fairway Analysis (PFA) in geothermal exploration originates from a systematic methodology developed within the petroleum industry and is based on a geologic, geophysical, and hydrologic framework of identified geothermal systems. We tailored this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region, but it can be adapted to other geothermal resource settings. We adapted the PFA approach to geothermal resource exploration by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building a code-based ‘processing model’ to process results. A geographic information system was used to compile a range of different data types, which we refer to as elements (e.g., faults, vents, heat flow, etc.), with distinct characteristics and measures of confidence. Discontinuous discrete data (points, lines, or polygons) for each element were transformed into continuous interpretive 2D grid surfaces called evidence layers. Because different data types have varying uncertainties, most evidence layers have an accompanying confidence layer which reflects spatial variations in these uncertainties. Risk layers, as defined here, are the product of evidence and confidence layers, and are the building blocks used to construct Common Risk Segment (CRS) maps for heat, permeability, and seal, using a weighted sum for permeability and heat, but a different approach with seal. CRS maps quantify the variable risk associated with each of these critical components. In a final step, the three CRS maps were combined into a Composite Common Risk Segment (CCRS) map, using a modified weighted sum, for results that reveal favorable areas for geothermal exploration. Additional maps are also presented that do not mix contributions from evidence and confidence (to allow an isolated view of evidence and confidence), as well as maps that calculate favorability using the product of components instead of a weighted sum (to highlight where all components are present). Our approach helped to identify areas of high geothermal favorability in the western and central Snake River Plain during the first phase of study and helped identify more precise local drilling targets during the second phase of work. By identifying favorable areas, this methodology can help to reduce uncertainty in geothermal energy exploration and development.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Classification scheme for sedimentary and igneous rocks in Gale crater, Mars

Rocks analyzed by the Curiosity rover in Gale crater include a variety of clastic sedimentary rocks and igneous float rocks transported by fluvial and impact processes. Here, to facilitate the discussion of the range of lithologies, we present in this article a petrological classification framework adapting terrestrial classification schemes to Mars compositions (such as Fe abundances typically higher than for comparable lithologies on Earth), to specific Curiosity observations (such as common alkali-rich rocks), and to the capabilities of the rover instruments. Mineralogy was acquired only locally for a few drilled rocks, and so it does not suffice as a systematic classification tool, in contrast to classical terrestrial rock classification. The core of this classification involves (1) the characterization of rock texture as sedimentary, igneous or undefined according to grain/crystal sizes and shapes using imaging from the ChemCam Remote Micro-Imager (RMI), Mars Hand Lens Imager (MAHLI) and Mastcam instruments, and (2) the assignment of geochemical modifiers based on the abundances of Fe, Si, alkali, and S determined by the Alpha Particle X-ray Spectrometer (APXS) and ChemCam instruments. The aims are to help understand Gale crater geology by highlighting the various categories of rocks analyzed by the rover. Several implications are proposed from the cross-comparisons of rocks of various texture and composition, for instance between in place outcrops and float rocks. All outcrops analyzed by the rover are sedimentary; no igneous outcrops have been observed. However, some igneous rocks are clasts in conglomerates, suggesting that part of them are derived from the crater rim. The compositions of in-place sedimentary rocks contrast significantly with the compositions of igneous float rocks. While some of the differences between sedimentary rocks and igneous floats may be related to physical sorting and diagenesis of the sediments, some of the sedimentary rocks (e.g., potassic rocks) cannot be paired with any igneous rocks analyzed so far. Finally, in contrast, many float rocks, which cannot be classified from their poorly defined texture, plot on chemistry diagrams close to float rocks defined as igneous from their textures, potentially constraining their nature.

58 GEOSCIENCES↗
DOE OSTI2016

U.S. DOE NETL methodology for estimating the prospective CO 2 storage resource of shales at the national and regional scale

While the majority of shale formations will serve as reservoir seals for stored anthropogenic carbon dioxide (CO2), hydrocarbon-bearing shale formations may be potential geologic sinks after depletion through primary production. Here in this paper we present the United States-Department of Energy-National Energy Technology Laboratory (US-DOE-NETL) methodology for screening-level assessment of prospective CO 2 storage resources in shale using a volumetric equation. Volumetric resource estimates are produced from the bulk volume, porosity, and sorptivity of the shale and storage efficiency factors based on formation-scale properties and petrophysical limitations on fluid transport. Prospective shale formations require: (1) prior hydrocarbon production using horizontal drilling and stimulation via staged, high-volume hydraulic fracturing, (2) depths sufficient to maintain CO 2 in a supercritical state, generally >800 m, and (3) an overlying seal. The US-DOE-NETL methodology accounts for storage of CO 2 in shale as a free fluid phase within fractures and matrix pores and as an sorbed phase on organic matter and clays. Uncertainties include but are not limited to poorly-constrained geologic variability in formation thickness, porosity, existing fluid content, organic richness, and mineralogy. Knowledge of how these parameters may be linked to depositional environments, facies, and diagenetic history of the shale will improve the understanding of pore-to-reservoir scale behavior, and provide improved estimates of prospective CO 2 storage.

25 ENERGY STORAGE↗
DOE OSTI2019

Managing well leakage risks at a geologic carbon storage site with many wells

Potential geologic carbon storage (GCS) sites with a history of oil and gas production have well-characterized injectivity and storage capacity, but the presence of legacy wells increases leakage risk. Thus, the success of GCS operations at sites with many wells will require a thorough leakage risk assessment and a robust strategy for managing well leakage risk over the lifetime of the project. In this study, we demonstrate a workflow that uses the National Risk Assessment Partnership’s open-source Integrated Assessment Model to quantify well leakage risks and test the performance of various leakage risk management strategies at a heavily drilled GCS site. Here, our model simulates a 50-year basin-scale injection of CO 2 at a hypothetical site based on the Kimberlina Project Site in the Southern San Joaquin Valley of California. Brine and CO 2 leakage through 1,000 legacy wells into a USDW are stochastically simulated as a proxy for risk. We consider multiple scenarios that explore the efficacy of various well leakage risk management strategies with changes in well leakage behavior, reservoir behavior, and post-injection site care (PISC) length. Predicted leakage at the site after 100 years was small with a maximum CO 2 leakage of 102.1 tonnes (4.08×10 -5 % of the 250 Mt injected) and a maximum brine leakage of 2.4 tonnes. Leakage risk management strategies based on accurate prior information about well leak probability reduced leakage risks more effectively at the modeled site and were more robust with respect to reservoir uncertainty than strategies based on the distance of the legacy well from the injector. The importance of the PISC period length was not clear as it had a negligible impact on CO 2 leakage risk but a sizable impact on brine leakage risk in our model.

58 GEOSCIENCES↗
DOE OSTI2022

Deep learning-accelerated 3D carbon storage reservoir pressure forecasting based on data assimilation using surface displacement from InSAR

Fast forecasting of the reservoir pressure distribution during geologic carbon storage (GCS) by assimilating monitoring data is a challenging problem. Due to high drilling cost, GCS projects usually have spatially sparse measurements from few wells, leading to high uncertainties in reservoir pressure prediction. To address this challenge, we use low-cost Interferometric Synthetic-Aperture Radar (InSAR) data as monitoring data to infer reservoir pressure build up. We develop a deep learning-accelerated workflow to assimilate surface displacement maps interpreted from InSAR and to forecast dynamic reservoir pressure. Employing an Ensemble Smoother Multiple Data Assimilation (ES-MDA) framework, the workflow updates three-dimensional (3D) geologic properties and predicts reservoir pressure with quantified uncertainties. We use a synthetic commercial-scale GCS model with bimodally distributed permeability and porosity to demonstrate the efficacy of the workflow. A two-step CNN-PCA approach is employed to parameterize the bimodal fields. The computational efficiency of the workflow is boosted by two residual U-Net based surrogate models for surface displacement and reservoir pressure predictions, respectively. The workflow can complete data assimilation and reservoir pressure forecasting in half an hour on a personal computer.

25 ENERGY STORAGE↗
DOE OSTI2022

Risk matrix for legacy wells within the Area of Review (AoR) of Carbon Capture & Storage (CCS) projects

The success of CCS depends on the capacity, injectivity, and confinement by the storage medium. Thousands of wells drilled over the past century with the intention to find the trapped oil and gas may penetrate the containment seals. These wells may provide leakage pathways for the CO 2 to escape and contaminate the underground sources of drinking water (USDW) or reach the surface in the worst-case scenario. Identifying the risky wells penetrating the containment seals and predicting their current as well as future well integrity is the most challenging task when limited data is available. Here, this paper proposes a unique methodology for risk assessment of the wells penetrating the containment seals based on the proximity of these wells from the proposed injection location, mechanical integrity, and accessibility of these wells over the lifecycle of the CCS project. This helps in identifying the wells which need immediate attention from the wells that need little to no attention. It also highlights the corrective actions necessary for the success of the CCS project as well as help estimate the approximate cost required to perform the corrective actions. This methodology focuses on all wells (producers, injectors, orphan, abandoned, water, stratigraphic, etc) while the majority of the studies found in literature focused on wells with sustained casing pressure (SCP) reports and cement bond logs (CBL). The proposed risk matrix, if applied to future CCS projects across the globe, will uniformly categorize the wells within the Area of Review (AoR).

58 GEOSCIENCES↗
DOE OSTI2025

Accurate and efficient predictions of keyhole dynamics in laser materials processing using machine learning-aided simulations

The keyhole phenomenon has been widely observed in laser materials processing, including laser welding, remelting, cladding, drilling, and additive manufacturing. Keyhole-induced defects, primarily pores, dramatically affect the performance of final products, impeding the broad use of these laser-based technologies. The formation of these pores is typically associated with the dynamic behavior of the keyhole. So far, the accurate characterization and prediction of keyhole features, particularly keyhole depth, as a function of time, has been a challenging task. In situ characterization of keyhole dynamic behavior using the synchrotron X-ray technique is informative but complicated and expensive. Current simulations are generally hindered by their poor accuracy and generalization abilities in predicting keyhole depths due to the lack of accurate laser absorptance data. In this study, we develop a machine learning-aided simulation method that accurately predicts keyhole dynamics, especially in keyhole depth fluctuations, over a wide range of processing parameters. In two case studies involving titanium and aluminum alloys, we achieve keyhole depth prediction with a mean absolute percentage error of 10 %, surpassing those simulated using the ray-tracing method with an error margin of 30 %, while also reducing computational time. This exceptional fidelity and efficiency empower our model to serve as a cost-effective alternative to synchrotron experiments. Our machine learning-aided simulation method is affordable and readily deployable for a large variety of materials, opening new doors to eliminate or reduce defects for a wide range of laser materials processing techniques.

Computational fluid dynamics↗
DOE OSTI2024

De-risking fault leakage risk and containment integrity for subsurface storage applications

The subsurface is pivotal in the energy transition, for the sequestration of CO 2 and energy storage. It is crucial to understand to what extent geological faults may form leakage pathways that threaten the containment integrity of these projects. Fault flow behavior has been studied in the context of hydrocarbon development, supported by observations from wells drilled through faults, but such observations are rare in geoenergy projects. Focusing on mechanical behavior as early indicator of potential leakage risks, a probabilistic Coulomb Failure Stress workflow is developed and demonstrated using data from the Decatur CO 2 sequestration project to rank faults based on their containment risk. The analysis emphasizes the importance of fault throw relative to reservoir thickness and pore pressure change in assessing reactivation risks. Integrating this mechanical assessment with geological and dynamic fault analyses contributes to derisking fault containment for geoenergy applications, providing valuable insights for the successful development of subsurface storage projects.

58 GEOSCIENCES↗
DOE OSTI2026

Finite-element boundary-integral simulation of thin wires and inhomogeneous penetrable bodies in subsurface multilayered anisotropic media

With the prevailing presence of drilling wells near the subsurface in mature oil and gas fields, the application of electromagnetic methods can be particularly challenging where the electromagnetic field is affected by the steel casing. In the past decades, borehole-to-surface and crosswell electromagnetic methods have been utilized for monitoring of reservoir and underground CO 2 storage. This paper presents a unified finite-element boundary-integral (FEBI) method capable of simultaneously modeling the complex electromagnetic interactions between thin metallic wires (representing steel casings) with 3D trajectory and arbitrary 3D inhomogeneous penetrable bodies (such as CO 2 plumes or hydrocarbon reservoirs) within anisotropic multilayered subsurface environments. Unlike existing approaches that treat these components separately or require dense discretization, or are limited to vertical wells, our unified formulation preserves flexible electromagnetic coupling while delivering improved computational efficiency. Assuming the background formation is multilayered anisotropic media, the surface integral equation method is applied to model the thin wires and boundaries of the inhomogeneous bodies. Meanwhile, the finite element method is applied to model the volume of inhomogeneous bodies. Here, the performance of the proposed FEBI method is assessed through comparison with reference numerical results and its practical significance is demonstrated through CO 2 plume monitoring scenarios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Contaminant point source localization error estimates as functions of data quantity and model quality

We develop empirically-grounded error envelopes for localization of a point contamination release event in the saturated zone of a previously uncharacterized heterogeneous aquifer into which a number of plume-intercepting wells have been drilled. We assume that flow direction in the aquifer is known exactly and velocity is known to within a factor of two of our best guess from well observations prior to source identification. Other aquifer and source parameters must be estimated by interpretation of well breakthrough data via the advection-dispersion equation. We employ high performance computing to generate numerous random realizations of aquifer parameters and well locations, simulate well breakthrough data, and then employ unsupervised machine optimization techniques to estimate the most likely spatial (or space-time) location of the source. Tabulating the accuracy of these estimates from the multiple realizations, we relate the size of 90% and 95% confidence envelopes to the data quantity (number of wells) and model quality (fidelity of ADE interpretation model to actual concentrations in a heterogeneous aquifer with channelized flow). We find that for purely spatial localization of the contaminant source, increased data quantities can make up for reduced model quality. For space-time localization, we find similar qualitative behavior, but significantly degraded spatial localization reliability and less improvement from extra data collection. Since the space-time source localization problem is much more challenging, we also tried a multiple-initial-guess optimization strategy. Furthermore, this greatly enhanced performance, but gains from additional data collection remained limited.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Coupling geophysical, geological, geochemical and mineralogical assessments to examine preferential contaminant transport pathways in interbedded fractured bedrock

This study shows that a multi-faceted approach, combining borehole geophysical logging and surface seismic P-wave first-arrival tomography with confirmatory coring, well installation, and chemical and mineralogical analysis, is effective for identifying difficult-to-locate preferential contaminant transport pathways in deeper fractured bedrock. Seismic tomography detected porous 10–20 m wide elongated fractured conduits that allow acidic groundwater contaminated with uranium (U) and nitrate (NO 3 - ) to migrate within interbedded shale-limestone bedrock over 1000 m from a former disposal facility (S-3 Ponds site) located at the DOE Y-12 National Security Complex in Tennessee (USA). Conventional drilling techniques would easily miss these conduits because they are oriented parallel with fractured bedding planes. Synchrotron analysis of aquifer solids revealed that > 95 % of the U is hexavalent (U VI ). This uranyl (UO 2 2+ ) species is coordinated with carbonate, iron oxide, silicate and phosphate minerals within cemented white to yellow precipitates, which contain U concentrations as high as ∼21.6 % by weight fraction. Identifying the presence of these mineral phases, enables a further understanding of the potential effectiveness of remediation actions. The combination of methodologies presented here can also be applied to other explorations, such as the detection of water supply.

Fate and transport↗
DOE OSTI2017

Periodic changes in effluent chemistry at cold-water geyser: Crystal geyser in Utah

Crystal geyser is a CO 2 -driven cold-water geyser which was originally drilled in the late 1930’s in Green River, Utah. By utilizing a suite of temporal groundwater sample datasets, in situ monitoring of temperature, pressure, pH and electrical conductivity from multiple field trips to Crystal geyser from 2007 to 2014, periodic trends in groundwater chemistry from the geyser effluent were identified. Based on chemical characteristics, the primary sourcing aquifers are characterized to be both the Entrada and Navajo Sandstones with a minor contribution from Paradox Formation brine. The single eruption cycle at Crystal geyser lasted over four days and was composed of four parts: Minor Eruption (mEP), Major Eruption (MEP), Aftershock Eruption (Ae) and Recharge (R). During the single eruption cycle, dissolved ionic species vary 0–44% even though the degree of changes for individual ions are different. Generally, Na + , K + , Cl - and SO 4 2- regularly decrease at the onset and throughout the MEP. These species then increase in concentration during the mEP. In contrast, Ca 2+ , Mg 2+ , Fe 2+ and Sr 2+ increase and decrease in concentration during the MEP and mEP, respectively. The geochemical inverse modeling with PHREEQC was conducted to characterize the contribution from three end-members (Entrada Sandstone, Navajo Sandstone and Paradox Formation brine) to the resulting Crystal geyser effluent. Results of the inverse modeling showed that, during the mEP, the Navajo, Entrada and brine supplied 62–65%, 36–33% and 1–2%, respectively. During the MEP, the contribution shifted to 53–56%, 45–42% and 1–2% for the Navajo, Entrada and Paradox Formation brine, respectively. Finally, these changes in effluent characteristics further support the hypothesis by Watson et al. (2014) that the mEP and MEP are driven by different sources and mechanisms.

54 ENVIRONMENTAL SCIENCES↗