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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.
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Datasets and information used to characterize the subsurface of Newberry and support modeling efforts. Includes sources for well logs, earthquakes, maps & cross-sections, and LiDAR/DEM
This is an executable python script which offers two different conversions for well log data: 1) Conversion from a BoreholeLASLogData.xls model to a LAS version 2.0 formatted XML file. 2) Conversion from a LAS 2.0 formatted XML file to an entry in the WellLog Content Model. Example templates for BoreholeLASLogData.xls and WellLogsTemplate.xls can be found in the package after download.
This is an executable python script which offers two different conversions for well log data: 1) Conversion from a BoreholeLASLogData.xls model to a LAS version 2.0 formatted XML file. 2) Conversion from a LAS 2.0 formatted XML file to an entry in the WellLog Content Model. Example templates for BoreholeLASLogData.xls and WellLogsTemplate.xls can be found in the package after download.
Establishing an Early CO2 Storage Complex in Kemper County, Mississippi (ECO2S): Geophysical Well Log Report (Deliverable 6.2.a)
Solving a non-linear inverse problem is challenging in computational science and engineering. Sampling based methods require a large number of model valuations; gradientbased methods require fewer model evaluations but only find the local minima. Multifidelity optimization combines the low fidelity model and the high-fidelity model to achieve both high accuracy and high efficiency. In this paper, we present a bi-fidelity approach to solve non-linear inverse problems. In the bi-fidelity inversion method, the low-fidelity model is used to acquire a good initial guess, and the high-fidelity model is used to locate the global minimum. Combined with a multi-start optimization scheme, the proposed approach significantly increases the possibility of finding the global minimum for nonlinear inverse problems with many local minima. The method is tested with two toy problems and then applied to an electromagnetic well logging inverse problem, which is difficult to solve using traditional gradient-based methods. The bi-fidelity method provides promising inversion results and can be easily applied to traditional gradient-based methods.
Use of conventional and shaly-sand well log analyses to identify and characterize the thickness and residual oil saturation of suspected ROZs beneath the main pay zones in the Cypress Sandstone at Noble and Kenner West Oil Fields, Illinois.
We report resistivity and acoustic logs are widely used to estimate gas hydrate saturation in various sedimentary systems using one of the two popular methods ((1) acoustic velocity and (2) electrical resistivity), but the limitations of these two methods are often overlooked, which include (i) well-specific calibration of empirical exponents in the electrical resistivity method, (ii) assumption of known pore morphology for gas hydrates in the acoustic velocity method, and (iii) presence of unknown mineralogy and bulk modulus terms in the acoustic velocity method. NMR-density porosity-derived gas hydrate saturation based on the analysis of the transverse magnetization relaxation time (T2) is considered the most precise method, but acquisition of NMR-based logs is limited at relatively recent drilled sites; additionally, its use in conventional oil and gas reservoirs is not that common due to higher cost and operational deployment limitations associated with acquiring NMR well-logs. This study proposes a new method that predicts gas hydrate saturation (S h ) for any well using porosity, bulk density, and compressional wave (P wave) velocity well-logs with neural network (or stochastic gradient descent regression) without any well-specific calibration and/or other aforementioned shortcomings of the existing methods. The method is developed by examining the underlying dependency between S h and different combinations of well-logs, chosen from 6 routine logs, with 12 different machine learning (ML) algorithms. The accuracy of the proposed method in predicting S h is ~ 84%, which is better than the accuracy of seismic and electrical resistivity methods (≤ 75%) per the results reported by three different studies. The robustness of the method in the specific case of permafrost-associated gas hydrates is demonstrated with well-log data from two wells drilled on the Alaska North Slope.
Southern Tunisia is an arid area where socio-economic activities are dependent on groundwater resources. The presented study aims to better characterize the Jurassic aquifer based on geological and geophysical data, with a view to develop a rational exploitation program. Well logs are used to precisely determine the position and composition of the known Jurassic aquifer layers and to identify others able to produce good quality water. The logs show that limestones, sandstones and dolomites of the Krachoua, Techout and Foum Tataouine formations are the main Jurassic aquifers. Sixty-eight seismic-reflection sections are integrated within this study. The interpolation between the interpreted sections leads to the construction of isochronous isopach maps and geoseismic sections, and their analysis finds that compressive and extensive tectonic deformations have influenced the Jurassic aquifer geometry. The Hercynian orogeny phase manifestation is remarkable in that there are several stratigraphic gaps in the Jurassic sequence. The E–W, NW–SE, and NNW–SSE accidents, reactivated in normal faults since the Permian to Lower Cretaceous epochs, have generated the structures found in the Jurassic series, such as subsided and raised blocks. Their syn-sedimentary activity has controlled the thickness and facies of these series. The Cretaceous, Tortonian and Post-Villafranchian compressions are responsible for the Jurassic-deposits folding in some localities. The highlighted tectonic and sedimentary events have an important impact on the Jurassic aquifer function by favoring the Jurassic aquifer interconnections and their connections with the Triassic and Cretaceous permeable series.
This work demonstrates how the characterization and modeling of both elastic and creep properties are essential to describe zones in layered rock formations as either low-stress targets for stimulation or high-stress barriers to fracture growth. Prediction of fracture height is critical for designing stimulation operations in oil and gas wells. Ideally, fractures are placed in target zones which will produce hydrocarbons and should not propagate into zones expected to be unproductive or to produce unwanted fluids such as water which in turn must be treated and/or disposed. The essential task in designing stimulation plans is predicting which zones have low horizontal stresses and which will be high-stress barriers to fracture growth. Despite this importance, there are gaps in current knowledge and a complete workflow from laboratory characterization to a finite element model which includes time dependent rock deformation is required. While the research and methodology presented here also have application to CO 2or hydrogen storage, wastewater injection, and geothermal applications, the focus will be on hydrocarbon extraction. This thesis presents the results of a characterization-to-prediction workflow for the Caney shale, which is an emerging hydrocarbon resource in Oklahoma, USA. It begins with an investigation to enable critical evaluation of the Caney zonation into nominally “brittle” and “ductile” zones based on properties observed from well logs. It shows none of the zones are consistently “brittle” or “ductile” mechanical behavior based on the variety of definitions of these terms. However, the nominally ductile zones are weaker and more prone to creep. A laboratory investigation of samples including strength, elastic, and creep properties, is then used in a finite element model of stress evolution. The model includes both elastic deformation and viscoplastic creep. Results predict the least creep-prone layers to have the lowest horizontal stresses, therefore comprising hydraulic fracturing targets. The most creep-prone layers attain a horizontal stress similar to the vertical stress and therefore are predicted to be high stress barriers to hydraulic fracture stimulation. In addition to defining stimulation target intervals, the model shows how as tectonic strain rate increases, there is a transition from creep-dominated stresses to stresses dominated by elasticity.
The Illinois Basin Decatur Project (IBDP) successfully demonstrated the safe geologic storage of carbon dioxide at a commercial scale. Within the IBDP project three deep wells (injection (CCS1), monitoring (VW1), geophysical (GM1)) were competed and geophysical logs were recorded. During injection and post-injection periods microseismic monitoring was conducted to create a miscoseismic catalog. The correlations between microseimic attributes and geomechanical well logs define major geomechanical drivers of microseismic expression to understand a reservoir response to CO2 injection in geological context. Utilizing standard sonic and density well logs, the dynamic elastic moduli were calculated and employed to correlate with microseismic pseudo-logs. A multi-dimensional Mu-rho and Lambda-rho (MRLR) hyperdimensional plots display of meaningful data and uncovered subtle relationships between elastic properties of sandstones and the seismological attributes of recorded microseismicity.
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The Terrebonne Basin is a salt bounded mini-basin in the northeast section of the Walker Ridge protraction area in the Gulf of Mexico, and the main site for an upcoming gas-hydrate focused International Ocean Discovery Program (IODP) cruise. The basin is infilled by an increasingly mud rich sedimentary sequence with several 5-15 meter gas-hydrate filled sand units of Miocene to Pliocene age overlying the up-domed salt. These gas-hydrate filled sand units can be identified in logging while drilling data from two existing wells in the Terrebonne Basin, drilled in 2009 by the Gas Hydrate Joint Industry Project (JIP) Leg 2. The sand units are cross cut by a distinct bottom-simulating reflector (BSR), and are clearly characterized by a polarity reversal in the sand units. The polarity reversal is caused by a positive gas-hydrate filled sand within the stability zone changing to negative gas-bearing sand. Using well data and calculated synthetic seismogram well ties we are able to identify several additional 1-4 meter gas-hydrate and water-saturated sand units associated with thick (100-200 m-thick), fine grained, hydrate bearing fractured units in the upper sedimentary sequence on the seismic data. Following on previous work, we propose that microbial generation of methane occurring within the fine-grained, fractured units acts as a source for gas hydrate formation in the thin sands. In contrast, it has been proposed that the gas hydrate in the 5-15 m-thick sands first discovered by the JIP was originates from a deeper thermogenic source. Through correlating hydrate occurrence in sands from well data, to amplitudes derived from the seismic data, we can estimate possible distribution of hydrate across the basin. Overall, we find the Terrebonne basin to be a complex gas hydrate system with multiple mechanisms of methane generation and migration.
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This is the full wireline geophysical datasets for characterization of the EGS Collab Experiment #1 testbed on the 4850 level. A metadata file is included within the dataset explaining the logs, fracture picks, etc. Eight boreholes were drilled for this testbed and each one was logged with north seeking gyro, optical televiewer, acoustic televiewer, fluid temperature conductivity, resistivity and gamma, and full waveform sonic. In these folders are the processed results as text, csv, and pdf files, along with the raw data which will need to be read using WellCAD software.