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Results for “WELL LOGGING”

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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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Electronic neutron sources for compensated porosity well logging

The viability of replacing Americium–Beryllium (Am–Be) radiological neutron sources in compensated porosity nuclear well logging tools with D–T or D–D accelerator-driven neutron sources is explored. The analysis consisted of developing a model for a typical well-logging borehole configuration and computing the helium-3 detector response to varying formation porosities using three different neutron sources (Am–Be, D–D, and D–T). The results indicate that, when normalized to the same source intensity, the use of a D–D neutron source has greater sensitivity for measuring the formation porosity than either an Am–Be or D–T source. The results of the study provide operational requirements that enable compensated porosity well logging with a compact, low power D–D neutron generator, which the current state-of-the-art indicates is technically achievable.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Improving multiwell petrophysical interpretation from well logs via machine learning and statistical models

Well-log interpretation estimates in situ rock properties along well trajectory, such as porosity, water saturation, and permeability, to support reserve-volume estimation, production forecasts, and decision making in reservoir development. However, due to measurement errors, variability of well logs caused by multiple measurement vendors, different borehole tools, and nonuniform drilling/borehole conditions, estimations of rock properties with original well logs without proper preprocessing may not be accurate, especially in the context of multiwell estimation. Well-log normalization techniques such as two-point scaling and mean-variance normalization are commonly used to improve the robustness of multiwell rock-property estimation. However, these techniques do not consider the correlation between well logs and require subjective knowledge for their effective implementation. To reduce uncertainties and processing time associated with multiwell rock-property estimation from well logs, we develop discriminative adversarial (DA) and linear constraint models for well-log normalization and rock-property estimation. The DA neural network model developed for well-log normalization and interpretation can perform linear and nonlinear well-log normalization while considering the joint distribution of each well log and rock properties. However, the linear constraint model uses an ensemble of predictions from linear models to constrain well-log normalization and rock-property estimation. We also develop a divergence-based type well identification method to select type (training) wells for a test well based on the statistical similarity of associated well-log distributions instead of the interwell distance. We apply the DA model to perform well-log normalization and prediction of permeability for the Seminole San Andres Unit carbonate reservoir. Compared with the permeability predicted with the classical machine learning model without well-log normalization and models with two-point scaling normalization, the DA model yields the most accurate permeability prediction by decreasing the mean-squared error of permeability prediction by 20%–50%.

Geochemistry & Geophysics↗
DOE OSTI2018

Fallon FORGE: Well Log Database

Master well database for all logs and other well data pertaining to the Fallon FORGE site. Tables are formatted in NGDS Teir 3 schema where appropriate; redundancies between tables are omitted, and should be queried off of the main WellHeader table. All relationships are set on the "HeaderURI" primary key. Tables: WellHeader - well locations and information ChemFluid - aqueous chemistry analyses ChemRock - rock chemistry analyses DensityCore - rock densities from core FracturesInduced - induced borehole fractures FracturesNatural - natural borehole factures LithIntercepts - lithology picks from cuttings and core MagSuscCore - magnetic susceptibility for core samples MagSuscPmag - magnetic susceptibility for pmag samples PTSLogs - pressure-temperature-spin logs WirelineLogs - digital wireline logs (21-31 only)

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Machine Learning for Well Log Analysis in Uranium Mining

This project explores the use of Artificial Intelligence (AI) and Machine Learning (ML) techniques to automate well log analysis for uranium mining. Geophysical log data—spontaneous potential, resistivity, and gamma ray—were used to classify lithology, correlate well logs and identify roll front zonation patterns, which are critical for locating uranium ore bodies. Supervised ML algorithms such as eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Random Forest were trained to classify lithology with high accuracy. Gradient Boosting Machines (GBM), XGBoost, Random Forest, and Neural Networks were also used for role front zone identification. Moreover, a Fast Dynamic Time Warping (FastDTW) algorithm was employed for well log correlation. Additionally, sample lag was addressed using dynamic programming. Results demonstrate the potential of AI and ML to streamline well log analysis and enhance uranium exploration workflows.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

SECARB Cranfield Well Logs

Borehole logs from the SECARB project at the Cranfield oil site in Franklin, Mississippi . Well logs are a part of the geologic characterization phase of SECARB; CFU 31F-1, CFU 31F-2, CFU 31F-3 well logs from Detailed Area of Study (DAS) and other well logs. Associated Publications: Butsch, R., Brown, A. L., Bryans, B., Kolb, C., Hovorka, S. D., 2013, Integration of well-based subsurface monitoring technologies: lessons learned at SECARB study, Cranfield, MS: International Journal of Greenhouse Gas Control https://doi.org/10.1016/j.ijggc.2013.06.010.

Borehole log↗
DOE OSTI2021

CarbonSafe II Project: Dryfork Station UW PRB 1 Well Core, Fluid, and Well Logs datasets

This dataset contains the raw data sets of thee UW PRB 1 well's geophysical well logs, core measurements and fluid analysis for the CarbonSafe II project at the Dryfork Station in Gillette, WY. Focus was placed on the Lakota, Hulett and Minnelusa Formations and their overlying seals. Also included are well logs from legacy wells from the surrounding area.

CarbonSafe 2↗
DOE OSTI2016

Oil & Natural Gas Technology A new approach to understanding the occurrence and volume of natural gas hydrate in the northern Gulf of Mexico using petroleum industry well logs

The northern Gulf of Mexico has been the target for the petroleum industry for exploration of conventional energy resource for decades. We have used the rich existing petroleum industry well logs to find the occurrences of natural gas hydrate in the northern Gulf of Mexico. We have identified 798 wells with well log data within the gas hydrate stability zone. Out of those 798 wells, we have found evidence of gas hydrate in well logs in 124 wells (15% of wells). We have built a dataset of gas hydrate providing information such as location, interval of hydrate occurrence (if any) and the overall quality of probable gas hydrate. Our dataset provides a wide, new perspective on the overall distribution of gas hydrate in the northern Gulf of Mexico and will be the key to future gas hydrate research and prospecting in the area.

03 NATURAL GAS↗
DOE OSTI2015

Experimental approaches for the development of gamma spectroscopy well logging system

This article discusses experimental approaches for the development of gamma spectroscopy well logging system. Considering the size of borehole sonde, we customize 2 x 2 inches inorganic scintillators and the system including high voltage, preamplifier, amplifier and multichannel analyzer (MCA). The calibration chart is made by test using standard radioactive sources so that the measured count rates are expressed by energy spectrum. Optimum high-voltage supplies and the measurement parameters of each detector are set up by experimental investigation. Also, the responses of scintillation detectors have been examined by analysis according to the distance between source and detector. Because gamma spectroscopy well logging needs broad spectrum, high sensitivity and resolution, the energy resolution and sensitivity as a function of gamma ray energy are investigated by analyzing the gamma ray activities of the radioactive sources.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Statistical analysis of pulsed-neutron well logs in monitoring injected carbon dioxide

Pulsed-neutron well logs (PNLs) were acquired to monitor CO 2 storage associated with enhanced oil recovery. This work quantifies the precision of repeat PNLs using data from four wells and 15 repeat PNLs. Root-mean-square (RMS) precision for the repeat PNLs was less than 3%, indicating good agreement between the baseline and repeat PNLs. Evaluations of scaled relative difference (Scaled-D) showed variation in precision among individual wells and formations. Analysis of false-positive rates (FPRs) across the entire data set showed that a Scaled-D threshold in sandstone formations of approximately ±8% resulted in a 1% FPR. These Scaled-D precision thresholds were used to estimate the value of CO 2 saturation able to be confidently distinguished from baseline. The detection limit for CO 2 is lowest for high-porosity formations filled with saline water and is highest for low-porosity formations filled with fresh water. Thus, detection of vertical out-of-zone CO 2 migration using repeat PNLs is a function of instrument precision, petrophysical properties, and hydrology, all of which must be taken into account as part of the monitoring program. Here, the results of this work provide insight into how PNLs may be included within monitoring plans to detect vertical out-of-zone CO 2 migration along a wellbore or instances of wellbore failure and provide a quantitative basis for establishing detection limits of repeat PNLs to distinguish change from baseline conditions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Application of Nuclear Well Logging Techniques to Lunar Resource Assessment

The use of neutron and gamma ray measurements for the analysis of material composition has become well established in the last 40 years. Schlumberger has pioneered the use of this technology for logging wells drilled to produce oil and gas, and for this purpose has developed neutron generators that allow measurements to be made in deep (5000 m) boreholes under adverse conditions. We also make ruggedized neutron and gamma ray detector packages that can be used to make reliable measurements on the drill collar of a rotating drill string while the well is being drilled, where the conditions are severe. Modern nuclear methods used in logging measure rock formation parameters like bulk density and porosity, fluid composition, and element abundances by weight including hydrogen concentration. The measurements are made with high precision and accuracy. These devices (well logging sondes) share many of the design criteria required for remote sensing in space; they must be small, light, rugged, and able to perform reliably under adverse conditions. We see a role for the adaptation of this technology to lunar or planetary resource assessment missions.

Albats, P.↗
DOE OSTI2022

General Overview of Mobile Sources Used for Well Logging and Industrial Radiography Applications

Mobile sources is a term most commonly used to describe radioactive sources that are used in applications requiring frequent transportation. Such radioactive sources are in common use world-wide where typical applications include radiographic non-destructive evaluation (NDE) and oil and gas well logging, among others requiring lesser amounts of radioactivity. This report provides a general overview of mobile sources used for well logging and industrial radiography applications including radionuclides used, equipment, and alternative technologies. Information presented here has been extracted from a larger study on common mobile radiation sources and their use.

47 OTHER INSTRUMENTATION↗
DOE OSTI2014

Boron-coated straw neutron detector for well-logging-Final Technical Report

The Oil & Gas exploration industry makes extensive use of radiation detectors for well logging – a geologic formation map that reveals crucial information for the viability of oil/gas extraction in surveyed wells. Helium-3 gas filled neutron detectors have been the gold standard for neutron porosity logs, one of two components in nuclear logging (gamma ray logs being the other component). The finite supply of 3He gas has dwindled in recent years due to an increased use in Homeland Security applications; therefore the need for alternative technologies that would ensure oil & gas exploration for coming years.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

A method of improving sensitivity of carbon/oxygen well logging for low porosity formation

Carbon/Oxygen (C/O) spectral logging technique has been widely used to determine residual oil saturation and the evaluation of water flooded layer. In order to improve the sensitivity of the technique for low – porosity formation, Gaussian and linear models are applied to fit the peaks of measured spectra to obtain the characteristic coefficients. Standard spectra of carbon and oxygen are combined to establish a new carbon /oxygen value calculation method, and the robustness of the new method is cross – validated with known mixed gamma ray spectrum. Formation models for different porosities and saturations are built using Monte Carlo method. The responses of carbon/oxygen which are calculated by conventional energy window method, and the new method is applied to oil saturation under low porosity conditions. The results show the new method can reduce the effects of gamma rays contaminated by the interaction between neutrons and other elements on carbon/oxygen ratio, and therefore can significantly improve the response sensitivity of carbon/oxygen well logging to oil saturation. The new method improves greatly carbon/oxygen well logging in low porosity conditions.

02 PETROLEUM↗
DOE OSTI2024

Integrating Experiments and Well Logs to Predict Caney Shale Static Mechanical Properties During Production with Supervised Machine Learning

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.

Kholy, Sherif M.↗