Global demand for lithium, the primary component of lithium-ion batteries, greatly exceeds known supplies and this imbalance is expected to increase as the world transitions away from fossil fuel energy sources. The goal of this work was to calculate the total lithium mass in brines of the Reynolds oolite unit of the Smackover Formation in southern Arkansas using predicted lithium concentrations from a machine-learning model. This research was completed collaboratively between the U.S. Geological Survey and the Arkansas Department of Energy and Environment—Office of the State Geologist. The Smackover Formation is a laterally extensive petroleum and brine system in the Gulf Coast region that includes locally high concentrations of bromide and lithium in southern Arkansas. This data release contains input files, Python scripts, and an R script used to prepare input files, create a random forest (RF) machine-learning model to predict lithium concentrations, and compute uncertainty in brines of the Reynolds oolite unit of the Smackover Formation in southern Arkansas. This data release also contains a Python script to calculate the total mass of lithium in brines of the Reynolds oolite unit of the Smackover Formation in southern Arkansas based on porosity. Knowledge of data-science and Python and R programming languages is a prerequisite for executing the workflow associated with this product. Users can execute the scripts to prepare input data, train a RF machine-learning model, compute uncertainty, and calculate lithium mass. Explanatory variables used to train the RF model included geologic, geochemical, and temperature data from either published datasets or created and documented in this data release and the associated companion publication (Knierim and others, 2024). See the associated metadata for details. This data release also includes output files (csvs [comma-delimited, plain-text] and rasters [geospatial grids]) of lithium concentration predictions from the RF model, uncertainty ranges, and lithium mass. The depth of prediction of lithium concentration represents the mid-point depth of the Reynolds oolite unit which varies between approximately 3,500 and 11,300 feet deep (below land-surface datum) and 0 and 400 feet thick across the model domain. For a full explanation of methods and results, see the companion manuscript Knierim and others (2024).

This lithium ground- and formation-water geochemical dataset will enable present and future companies to better evaluate their targets and characterize their resource estimates by being able to distinguish between background and anomalous concentrations of lithium throughout Alberta. The dataset comprises lithium geochemical data from ground and formation water in Alberta and near the Alberta border. The data were captured from several databases, including those from Alberta Geological Survey (oil and gas wells database, AERI and Beaver River Basin projects), and the Alberta Research Council. In total there are 1,511 records, of which 48 records have >75 mg/L Li. Nineteen analyses have >100 mg/L Li (up to 140 mg/L) and occur within the Middle to Upper Devonian Beaverhill Lake Formation and Woodbend and Winterburn groups of west-central to northwestern Alberta. Economic concentrations of lithium are known to form in either lithium pegmatite or in high-lithium brine and clay. A few of the world's oil-field waters also have medium to high lithium content. During the mid-1990s, several government reports showed that lithium values of up to 140 mg/L Li occurred in west-central Alberta formation waters of the Beaverhill Lake and Woodbend groups. however, minimal data were publicly released.

This data release provides the descriptions of approximately 20 U.S. sites that include mineral regions, mines, and mineral occurrences (deposits and prospects) that contain enrichments of lithium (Li). This release includes sites that have a contained resource and (or) past production of lithium metal greater than 15,000 metric tons. Sites in this database occur in Arkansas, California, Nevada, North Carolina, and Utah. There are several deposits that were not included in the database because they did not meet the cutoff requirement, and those occur in Arizona, Colorado, the New England area, New Mexico, South Dakota, and Wyoming. In the United States, lithium was first mined from pegmatite orebodies in South Dakota in the late 1800s. The Kings Mountain pegmatite belt of North Carolina also had significant production from pegmatites, and the area may still contain as much as 750 million metric tons (Mt) of ore containing 5 Mt lithium metal (Kesler and others, 2012). In 2018, U.S. production of lithium was restricted to a single lithium-brine mining operation in Nevada. In 2018, the U.S. had a net import reliance as a percentage of apparent consumption of more than 50 percent for lithium (U.S. Geological Survey, 2019). The U.S. is not a significant producer of lithium, so the commodity is mainly imported from Chile and Argentina to meet consumer demand. Lithium is necessary for strategic, consumer, and commercial applications. The primary uses for lithium are in batteries, ceramics, glass, metallurgy, pharmaceuticals, and polymers (U.S. Geological Survey, 2019). Lithium has excellent electrical conductivity and low density (lithium metal will float on water), making it an ideal component for battery manufacturing. Lithium is traded in three primary forms: mineral concentrates, mineral compounds (from brines), and refined metal (electrolysis from lithium chloride). Lithium mineralogy is diverse; it occurs in a variety of pegmatite minerals such as spodumene, lepidolite, amblygonite, and in the clay mineral hectorite. Current global production of lithium is dominated by pegmatite and closed-basin brine deposits, but there are significant resources in lithium-bearing clay minerals, oilfield brines, and geothermal brines (Bradley and others, 2017). The entries and descriptions in the database were derived from published papers, reports, data, and internet documents representing a variety of sources, including geologic and exploration studies described in State, Federal, and industry reports. Resources extracted from older sources might not be compliant with current rules and guidelines in minerals industry standards such as National Instrument 43-101 (NI 43-101) or the Joint Ore Reserves Committee Code (JORC Code). The inclusion of a particular lithium mineral deposit in this database is not meant to imply that the deposit is currently economic. Rather, these deposits were included to capture the characteristics of the larger lithium deposits in the United States, which are diverse in their geology and resource potential. Inclusion of material in the database is for descriptive purposes only and does not imply endorsement by the U.S. Government. The authors welcome additional published information in order to continually update and refine this dataset. Bradley, D.C., Stillings, L.L., Jaskula, B.W., Munk, LeeAnn, and McCauley, A.D., 2017, Lithium, chap. K of Schulz, K.J., DeYoung, J.H., Jr., Seal, R.R., II, and Bradley, D.C., eds., Critical mineral resources of the United States—Economic and environmental geology and prospects for future supply: U.S. Geological Survey Professional Paper 1802, p. K1–K21, https://doi.org/10.3133/pp1802K. Kesler, S.E., Gruber, P.W., Medina, P.A., Keoleian, G.A., Everson, M.P., and Wallington, T.J., 2012, Global lithium resources—relative importance of pegmatite, brine and other deposits: Ore Geology Reviews, v. 48, October ed., p. 55—69. U.S. Geological Survey, 2019, Mineral commodity summaries 2019:

This work was developed to complement the geochemical assessments of produced water and geothermal water samples. Specifically, this task was designed to test the influence of reservoir rock-type and corresponding mineralogy/geochemistry on the concentrations of REE found in oil and gas produced waters. There has been no direct investigation of REE reactions relative to rock-type in deep oil and gas brine prior to this investigation.

Batch tests of cross-linked lithium and manganese imprinted polymers of variable composition to assess their ability to extract lithium and manganese from synthetic brines at T=45 deg C .

This data release is a collection of quantitative and qualitative data for fluid inclusions in samples from the Bear Lodge alkaline complex, Wyoming. The dataset includes:microthermometry, Raman spectroscopy, noble gas spectroscopy, laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), and energy dispersive X-ray analyses of fluid inclusions. For spatial context and textural characterization, annotated scans of both sample thin sections, annotated photomicrographs of targeted fluid inclusion areas, cathodoluminescence images, and backscatter electron images of decrepitate mounds are also included.