Publications

Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 13.4 billion barrels of oil and 244.4 trillion cubic feet of gas in nine geologic provinces of China.

No abstract available.

The U.S. Geological Survey (USGS) assesses potential for undiscovered, technically recoverable oil and gas resources in priority geologic provinces and quantifies resource volume estimates within subdivisions called assessment units (AUs). AU boundaries are defined by USGS geologists using quantitative and qualitative geologic information. Variables contained in IHS Markit’s well and...

This Interagency Agreement supports the U.S. Department of Energy (DOE) and its research partners in understanding, predicting, and testing the recoverability and potential production characteristics of onshore natural gas hydrate in the Greater Prudhoe Bay area on the Alaska North Slope (ANS: Prudhoe Bay, Kuparuk River, and Milne Point areas) or other areas deemed suitable by DOE and...

Executive Summary Managers of our Nation’s resources face unprecedented challenges driven by the convergence of increasing, competing societal demands and a changing climate that affects the stability, vulnerability, and predictability of those resources. To help meet these challenges, the scientific community must take advantage of all available technologies, data, and integrative Earth...

The widespread application of directional drilling and hydraulic fracturing technologies expanded oil and gas (OG) development to previously inaccessible resources. A single OG well can generate millions of liters of wastewater, which is a mixture of brine produced from the fractured formations and injected hydraulic fracturing fluids (HFFs). With thousands of wells completed each year...

This entry defines and discusses the random forest machine learning algorithm. The algorithm is used to predict class or quantities for target variables using values of a set of predictor variables. It uses decision trees that are generated from bootstrap sampling of the training data set to create a "forest". The entry discusses the algorithm steps, the interpretative tools of the...

The Arctic Alaska Composite Tectono-Sedimentary Element (AA CTSE) as defined for this volume comprises Mississippian to Lower Cretaceous strata beneath the Alaska North Slope and the Beaufort and Chukchi Seas of the Arctic Ocean. The AA CTSE rests on Devonian and older sedimentary and metasedimentary rocks, considered economic basement for petroleum, and is overlain by Cretaceous to...

Medicine Lake Highlands/Fall River Springs Aquifer System, located in northeastern California, is home to some of the largest first-order springs in the United States. This work assesses the likely effects of projected climate change on spring flow. Four anticipated climate futures (GFDL A2, GFDL B1, CCSM4 rcp 8.5, CNRM rcp 8.5) for California, which predict a range of conditions...

Artificial neural networks (ANNs) are adaptable systems that can solve problems that are difficult to describe with a mathematical relationship. They seek relationships between different types of datasets with their abilities to learn either with supervision or without. ANNs recognize patterns between input and output space and generalize solutions, in a way simulating the human brain’s...

This report provides a step-by-step method for compiling hydraulic fracturing data in the United States from the IHS Markit, 2019, U.S. Well History and Production Relational Database. Data on hydraulically fractured wells include their location (geologic province, State, county), well type (oil or gas), orientation (directional, horizontal, or vertical), spud date, completion date and...

No abstract available.