Ryan R McShane

R scripts and results of estimated water use associated with continuous oil and gas development, Permian Basin, United States, 2010–19 (ver. 2.0, April, 2022)

For more than 100 years, the Permian Basin has been an important source of oil and gas produced from conventional reservoirs; directional drilling combined with hydraulic fracturing has greatly increased production in the past 10 years to the extent that the Permian Basin is becoming one of the world’s largest continuous oil and gas (COG) producing fields (U.S. Energy Information Administration, 2020). These recent techniques extract oil and gas by directionally drilling and hydraulically fracturing the surrounding reservoir rock. The extraction of COG by using these techniques requires large volumes of water and estimates of the total water volume used in COG require a comprehensive assessment to determine the...

Categories: Data Release - Revised; Tags: New Mexico, Permian Basin, Texas, USGS Science Data Catalog (SDC), computational methods, All tags... environment, regression analysis, statistical analysis, visualization methods, water use, Fewer tags

PRISM Yearly Mean Air Temperature and Precipitation for Select Counties in New Mexico and Texas, 1981-2019

This child page contains PRISM yearly mean air temperature and precipitation covering select counties in New Mexico and Texas, 1981-2019. All data points that met the filtering criteria as described in the Data Processing <procdesc> steps were retained in the data release. Further filtering of data points to remove unrealistic values was done prior to modeling. The data was utilized as input data for the model associated with the Scientific Investigations Report "Estimates of Water Use Associated with Continuous Oil and Gas Development in the Permian Basin, Texas and New Mexico, 2010–2019" (Valder and others, 2021). The model was used to estimate water use associated with continuous oil and gas development in the...

Categories: Data; Tags: New Mexico, Texas, air temperature, precipitation

This metadata record describes model outputs and supporting model code for the Data-Driven Drought Prediction project of the Water Resources Mission Area Drought Program. The data listed here include outputs of multiple machine learning model types for predicting hydrological drought at select locations within the conterminous United States. The child items referenced below correspond to different models and spatial extents (Colorado River Basin region or conterminous United States). See the list below or metadata files in each sub-folder for more details. Daily streamflow percentile predictions for the Colorado River Basin region — Outputs from long short-term memory (LSTM) deep learning models corresponding to...

Tags: Conterminous United States, Hydrology, USGS Science Data Catalog (SDC), Upper Colorado River, climatologyMeteorologyAtmosphere, All tags... deep learning, drought prediction, droughts, hydrology, long short-term memory, machine learning, modeling, river systems, statistical analysis, streamflow, streamflow percentiles, streamflow predictions, Fewer tags

One of the largest conventional oil reservoirs in the United States, the Permian Basin, is becoming one of the world’s largest continuous oil and gas producing reservoirs. Continuous, or horizontal well drilling techniques extract oil and gas by directionally drilling and hydraulically fracturing the surrounding reservoir rock. The continuous extraction of oil and gas using hydraulic fracturing requires large volumes of water, and estimates of the total water volume used in the Continuous Oil and Gas (COG) extraction technique, requires a comprehensive assessment to determine the amount of water needed to extract reservoir resources. This data release contains the input and output files utilized for the assessment...

Tags: Energy Resources, USGS Science Data Catalog (SDC), Water Resources

Data-Driven Drought Prediction Project Model Outputs: Daily Streamflow and Streamflow Percentile Predictions for the Colorado River Basin Region

This metadata record describes outputs from 12 configurations of long short-term memory (LSTM) models which were used to predict streamflow drought occurrence at 384 stream gage locations in the Colorado River Basin region. The models were trained on data from 01-Oct-1981 to 31-Mar-2005 and validated over the period of record spanning 01-Apr-2005 to 31-Mar- 2014. The models use explanatory variable inputs described in Wieczorek (2023) (doi.org/10.5066/P98IG8LO) to predict daily streamflow and streamflow percentiles as described in Simeone (2022) (doi.org/10.5066/P92FAASD). Separate models were trained to predict daily streamflow and streamflow percentiles. Two types of percentiles were modeled: (1) fixed-threshold...

Categories: Data; Tags: Colorado River Basin, climatologyMeteorologyAtmosphere, deep learning, drought prediction, droughts, All tags... hydrology, long short-term memory, machine learning, modeling, river systems, statistical analysis, streamflow, streamflow percentiles, streamflow predictions, Fewer tags