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USGS2026

Quantitative mineral resource assessment of lithium pegmatite deposits in the southern Appalachian orogen

The first quantitative mineral resource assessment for undiscovered lithium pegmatite deposits in the southern Appalachian region of the United States was conducted. Permissive tracts for lithium pegmatite deposits were delineated by integrating lithological, tectonic, geochemical, geophysical and mineral occurrence data. Lithium pegmatite prospectivity of the tracts was ranked with simplified mappable criteria, including proximity to Paleozoic felsic intrusions and major lithotectonic structures, stream sediment geochemical anomalies, and pegmatite occurrence data. The geospatial data and permissive tracts were used to estimate the number of undiscovered lithium pegmatite deposits. These estimates were integrated into probabilistic simulations along with a new global lithium pegmatite grade and tonnage dataset to quantify potential contained undiscovered lithium resources. An economic filter was applied to convert the probabilistic estimates of contained lithium into recoverable material. The identified lithium pegmatite resources for the Carolina Lithium and Kings Mountain deposits, North Carolina, contain 1589 thousand tons (kt) of Li 2 O. The median contained undiscovered resource for the southern Appalachian orogen was estimated to be 2240 kt Li 2 O. At 90% confidence, the region contains at least 130 kt Li 2 O, and 10,700 kt at 10% confidence. After applying economic filters, the median recoverable contained resource was 1430 kt Li 2 O, corresponding to approximately 201 years of current lithium imports for consumption in the United States. North and South Carolina are likely to contain most of these resources. Coarse data resolution and intra-state variations in the geological data contribute to uncertainty of undiscovered lithium pegmatite resources. Continued efforts to harmonize disparate geospatial datasets with updated or new information can improve the accuracy and precision of estimated undiscovered lithium pegmatite resources in the study area and at broader scales.

Alabama, Georgia, Maryland, North Carolina, South ↗

USGS2019

Demonstrating the value of Earth observations—methods, practical applications, and solutions—group on Earth observations side event proceedings

Executive Summary The U.S. Geological Survey, the National Oceanic and Atmospheric Administration, the European Association for Remote Sensing Companies, and the European Space Agency in coordination with the GEOValue Community hosted a side event to the Group on Earth Observations Plenary on October 23–24, 2017, in Washington, D.C. The workshop, entitled “Demonstrating the Value of Earth Observations: Methods, Practical Applications and Solutions,” brought together more than 60 international experts including economists, scientists, and engineers to consider the state of the science and applications of valuing Earth observations (EO). This 2-day workshop built upon previous activities developed under the GEOValue initiative. This workshop brought together expert analysts from multiple disciplines and backgrounds who are developing methods to identify and measure the value of information generated from the use of satellite and in-situ data. The mix of government agencies, international financial institutions, and independent consultants who participated in the workshop blended to develop a rich mix of views, approaches, and outcomes. During the first part of the workshop, the focus was on the latest science in valuing EO. A number of methodologies were described. Approaches generally assess the societal benefits of specific actions (for example, investments in EO). Some methods focus on broad measures of economic activity (for example, gross domestic product) or methods to assess total economic value such as contingent valuation surveys. Alternatively, use-case approaches (a use case is defined as an evaluation in which one or more decisions, applications, or other uses of data, information, and information products are specifically considered) start with the specific actions and how information is used to support decision making and affect outcomes. The second part of the meeting was focused on the use and development of value chains and decision trees. A value chain can be defined as the set of value-adding activities that one or more organizations perform in creating and distributing goods and services. In terms of EO, the value chain approach can be applied to consider societal benefits of the data and assess the value of data and data features. The EO value chain considers the geospatial data sources and the processing of the data into value added information to be incorporated into decision-support systems, leading to decision makers’ actions. To understand the value of EO, one would also need to recognize the demand side of the equation or how EO benefits users. Extending the value chain concept and incorporating tenets of Bayesian decision making, a decision tree would include one or more use cases. The value provided by the marginal increase in information could flow from one or several parts of the supply side of the value chain. The decision tree is based on the premise that information has no value if it is not used in at least one decision. By connecting the value chain and the decision tree, a framework is created that allows for conceptualizing the value of EO in its many uses. One can then apply economic techniques to monetize the marginal benefit of an outcome with information versus one without. A third part of the meeting applied the value chain and decision-tree frameworks to five specific thematic areas, each with the focus of using information for a decision point: Effect of increasing temperatures on human health; Flooding—Mitigating, managing, and avoiding impacts to safety and property damage; Harmful algal blooms—Effects on human health, recreation, and tourism; Energy and mineral supply—Mitigating, managing, and avoiding impacts of shortfalls on the economy; and Effects of natural hazards on transportation systems—Effects on mobility, safety, and the economy. During the working session, five separate groups worked to define and delineate the value chains and decision trees associated with each topic, discussing the related challenges and data needs. The outcomes were reported back to the full group. Because of the complexity of the topics, most groups first identified a network of value chains and then narrowed the scope to develop a single value chain to address their group’s topic. Although they worked separately and on different topics, the groups came to similar conclusions, concurring that the value chain and decision-tree frameworks are very effective for informing quantitative impact assessments and developing a relatable narrative to assist the public in understanding the link between EO and citizens.

Open-File Report↗

USGS2023

Broadening benefits and anticipating tradeoffs with a proposed ecosystem service analysis framework for the US Army Corps of Engineers

Would-be adopters of ecosystem service analysis frameworks might ask, ‘Do such frameworks improve ecosystem service provision or social benefits sufficiently to compensate for any extra effort?’ Here we explore that question by retrospectively applying an ecosystem goods and services (EGS) analysis framework to a large river restoration case study conducted by the US Army Corps of Engineers (USACE) and comparing potential time costs and outcomes of traditional versus EGS-informed planning. USACE analytic methods can have a large influence on which river and wetland restoration projects are implemented in the United States because they affect which projects or project elements are eligible for federal cost-share funding. A new framework is designed for the USACE and is primarily distinguished from current procedures by adding explicit steps to document and compare tradeoffs and complementarity among all affected EGS, rather than the subset that falls within project purposes. Further, it applies economic concepts to transform ecological performance indicators into social benefit indicators, even if changes cannot be valued. We conclude that, for large multi-partner restoration projects like our case study, using the framework provides novel information on social outcomes that could be used to enhance project design, without substantially increasing scoping costs. The primary benefits of using the framework in the case study appeared to stem from early comprehensive identification of stakeholder interests that might have prevented project delays late in the process, and improving the communication of social benefits and how tradeoffs among EGS benefits were weighed during planning.

Missouri↗

USGS1981

Design of exploration and minerals-data-collection programs in developing areas

This paper considers the practical problem of applying economic analysis to designing minerals exploration and data collection strategies for developing countries. Formal decision rules for the design of government exploration and minerals-data-collection programs are derived by using a minerals-industry planning model that has been extended to include an exploration function. Rules derived are applicable to centrally planned minerals industries as well as market-oriented minerals sectors. They pertain to the spatial allocation of exploration effort and to the allocation of activities between government and private concerns for market-oriented economies. Programs characterized by uniform expenditures, uniform information coverage across regions, or uniform-density grid drilling progrmas are shown to be inferior to the strategy derived. Moreover, for market-oriented economies, the economically optimal mix in exploration activities between private and government data collection would require that only private firms assess local sites and that government agencies carry out regional surveys.

Socio-Economic Planning Sciences↗

USGS2011

A framework for sustainable invasive species management: environmental, social and economic objectives

Applying the concept of sustainability to invasive species management (ISM) is challenging but necessary, given the increasing rates of invasion and the high costs of invasion impacts and control. To be sustainable, ISM must address environmental, social, and economic factors (or *pillars*) that influence the causes, impacts, and control of invasive species across multiple spatial and temporal scales. Although these pillars are generally acknowledged, their implementation is often limited by insufficient control options and significant economic and political constraints. In this paper, we outline specific objectives in each of these three *pillars* that, if incorporated into a management plan, will improve the plan's likelihood of sustainability. We then examine three case studies that illustrate how these objectives can be effectively implemented. Each pillar reinforces the others, such that the inclusion of even a few of the outlined objectives will lead to more effective management that achieves ecological goals, while generating social support and long-term funding to maintain projects to completion. We encourage agency directors and policy-makers to consider sustainability principles when developing funding schemes, management agendas, and policy.

Journal of Environmental Management↗

USGS1999

Two valuation questions in one survey: Is it a recipe for sequencing and instrument context effects?

Economic theory suggests that willingness to pay for two goods independently offered should remain unchanged when the survey instrument changes slightly. Four survey treatments consisting of comprehensive good and a subset of that good were used. The surveys alternated in the question ordering and in the embedded good which accompanied the comprehensive good. We tested for sequencing and instrument context effects using both a combined and split sample designs. In the combined sample case we found some evidence to sequencing effects in the data containing the first subset good. Likelihood ratio tests indicated that sequencing did not effect scale or location of parameters. In the test for instrument context effects, evidence was found indicating context does effect willingness to pay estimates.

Applied Economics↗

USGS2025

Valuing recreational fishing using creel survey statistics

Recreation demand analysis has relied on mail and internet surveys to collect information on individual recreators. However, conducting these surveys is costly and time-consuming. Alternative sources that report aggregate visitation may go unused due to a lack of information about trip starting points. We set up and solve a system of equations that predict reservoir visits and the home locations of recreational anglers. Using mode-level effort statistics from Nebraska creel surveys, we separate the effects of travel cost and site attributes between bank and boat anglers, which allows us to measure heterogenous values for public reservoir access.

Nebraska↗

USGS2024

Understanding key mineral supply chain dynamics using economics-informed material flow analysis and Bayesian optimization

The low-carbon energy transition requires significant increases in production for many mineral commodities. Understanding demand, technological requirements, and prices associated with this production increase requires understanding the supply chain dynamics of many minerals simultaneously, and via a consistent framework. A generalized economics-informed material flow method, global materials modeling using Bayesian optimization, captures the market dynamics of key mineral commodities. The method relies only on a limited set of widely available historical data as input, enabling quantification of economic relationships (elasticities) for supply chain components where data are sparse, and relationships cannot be obtained via traditional statistical approaches. Building upon established material flow analysis (MFA) and economic modeling techniques, Bayesian optimization was applied to fit an economics-informed MFA model to global historical demand, supply, and price for aluminum, copper, gold, lead, nickel, silver, iron, tin, and zinc. This approach enables estimates for the evolution of ore grades, mine costs, refining charges, sector-specific demand, and scrap collection for each commodity. Economic relationships were quantified and compared with a database compiled from the literature, including 1333 values from 213 analyses across 65 publications. Discrepancies in methods and limited coverage make use of these parameters in modeling efforts difficult. This work provides a single, homogeneous, probabilistic approach to identifying economic relationships across mineral supply chains, with uncertainty quantification, a literature database for comparison, and a modeling framework in which to use them. This article met the requirements for a Gold-Gold JIE data openness badge described at http://jie.click/badges .

Journal of Industrial Ecology↗

USGS2013

Economic vulnerability to sea-level rise along the northern U.S. Gulf Coast

The northern Gulf of Mexico coast of the United States has been identified as highly vulnerable to sea-level rise, based on a combination of physical and societal factors. Vulnerability of human populations and infrastructure to projected increases in sea level is a critical area of uncertainty for communities in the extremely low-lying and flat northern gulf coastal zone. A rapidly growing population along some parts of the northern Gulf of Mexico coastline is further increasing the potential societal and economic impacts of projected sea-level rise in the region, where observed relative rise rates range from 0.75 to 9.95 mm per year on the Gulf coasts of Texas, Louisiana, Mississippi, Alabama, and Florida. A 1-m elevation threshold was chosen as an inclusive designation of the coastal zone vulnerable to relative sea-level rise, because of uncertainty associated with sea-level rise projections. This study applies a Coastal Economic Vulnerability Index (CEVI) to the northern Gulf of Mexico region, which includes both physical and economic factors that contribute to societal risk of impacts from rising sea level. The economic variables incorporated in the CEVI include human population, urban land cover, economic value of key types of infrastructure, and residential and commercial building values. The variables are standardized and combined to produce a quantitative index value for each 1-km coastal segment, highlighting areas where human populations and the built environment are most at risk. This information can be used by coastal managers as they allocate limited resources for ecosystem restoration, beach nourishment, and coastal-protection infrastructure. The study indicates a large amount of variability in index values along the northern Gulf of Mexico coastline, and highlights areas where long-term planning to enhance resiliency is particularly needed.

Alabama;Florida;Louisiana;Mississippi;Texas↗

USGS2022

Analysis of provisioning ecosystem services and perceptions of climate change for indigenous communities in the Western Himalayan Gurez Valley, Pakistan

Climate change is a significant threat to people living in mountainous regions. It is essential to understand how montane communities currently depend especially on the provisioning ecosystem services (ES) and the ways in which climate change will impact these services, so that people can develop relevant adaptation strategies. The ES in the Gurez Valley, in the Western Himalayas of Pakistan, provide a unique opportunity to explore these questions. This understudied area is increasingly exposed not only to climate change but also to the overexploitation of resources. Hence, this study aimed to (a) identify and value provisioning ES in the region; (b) delineate indigenous communities’ reliance on ES based on valuation; and (c) measure the perceptions of indigenous communities of the impact of climate change on the ES in Gurez Valley. Semi-structured interviews and focus group discussions were used to classify the provisioning ES by using the ‘Common International Classification on Ecosystem Services’ (CICES) table and applying the ‘Total Economic Valuation (TEV)’ Framework. Results indicate that the indigenous communities are highly dependent on ES, worth 6730 ± 520 USD/Household (HH)/yr, and perceive climate change as a looming threat to water, crops, and rearing livestock ESS in the Gurez Valley. The total economic value of the provisioning ES is 3.1 times higher than a household’s average income. Medicinal plant collection is a significant source of revenue in the Valley for some households, i.e., worth 766 ± 134.8 USD/HH/yr. The benefits of the sustainable use of ES and of climate change adaptation and mitigation, are culturally, economically, and ecologically substantial for the Western Himalayans.

Gurez Valley, Himalaya↗

USGS2026

Spatially referenced watershed models for the binational Red–Assiniboine River Basin: Bayesian vs frequentist comparison

Excess nutrient loading remains a leading cause of declining water quality in lakes, estuaries, and coastal waters worldwide, with global economic costs of US$200 billion – US$2 trillion annually from impacts on fisheries, tourism, freshwater resources, and water treatment. Our study focuses on total phosphorus (TP) in Lake Winnipeg and its binational Red-Assiniboine River Basin, where nutrient inputs have degraded water quality and increased cyanobacterial blooms. These changes pose ecological, public health, and economic risks. We applied a spatially referenced watershed model with a hybrid statistical-mechanistic structure partitioning annual nutrient loads into land-use export, land-to-water delivery, and in-reservoir decay. Bayesian and traditional frequentist model calibrations were compared. In the frequentist model, coefficients for agricultural inputs, forests /wetlands, stream channels, precipitation, and reservoir losses were statistically significant, whereas coefficient for wastewater was not. In contrast, all variables were successfully calibrated using the Bayesian approach. Model results delineate TP-export hotspots across the basin, showing that 54–62% of TP originates from the U.S., with agricultural sources ranging 62–72%—highlighting the importance of agriculture-focused Best Management Practices. Given the global relevance of nutrient-driven water-quality challenges, our results highlight Bayesian calibration for robust risk assessment and adaptive nutrient management.

Red–Assiniboine River Basin↗

USGS2020

Cost-effective fuel treatment planning: A theoretical justification and case-study

Modelling the spatial prioritisation of fuel treatments and their net effect on values at risk is an important area for applied work as economic damages from wildfire continue to grow. We model and demonstrate a cost-effective fuel treatment planning algorithm using two ecosystem services as benefits for which fuel treatments are prioritised. We create a surface of expected fuel treatment costs to incorporate the heterogeneity in factors affecting the revenue and costs of fuel treatments, and then prioritise treatments based on a cost-effectiveness ratio to maximise the averted loss of ecosystem services from fire. We compare treatment scenarios that employ cost-effectiveness with those that do not, and use common tools and models in a case study of the Sisters Ranger District on the Deschutes National Forest in central Oregon, USA. Using cost-effectiveness not only increases the expected averted losses from fuel treatments, but it also allows a larger area to be treated for the same cost, simply by incorporating costs and cost-effectiveness into the prioritisation routine. These results have considerable implications for policymakers and land managers trying to minimise risk. Incorporating costs into the spatial planning of treatments could allow more effective outcomes without increasing fuel treatment budgets.

Oregon↗

USGS2026

Evaluating machine learning approaches to identify and predict oil and gas produced water lithium concentrations

Recently, the demand for battery-grade lithium has substantially increased, largely due to electrification of the transportation sector. The search for new lithium sources has turned to produced waters (frequently brines), a large-volume wastewater by-product of oil and gas extraction. Geochemical analysis indicates the presence of varying concentrations of lithium from produced water samples collected across the United States and represented in the U.S. Geological Survey’s National Produced Water Geochemical Database, as well as mixtures of Marcellus Shale produced water included in the Pennsylvania Department of Environmental Protection’s Oil and Gas Well Waste Reports. We first examined whether the geochemical signature of the lithium-bearing produced waters is sufficiently distinct so that machine learning (ML) can be used to correctly classify samples to the formation of origin. The produced water sample data used to assess classification accuracy were from the Marcellus Shale, Utica Shale and Point Pleasant Formation (Utica), and Smackover Formation oil and gas wells. Further, we evaluated the potential for ML to accurately classify Marcellus Shale produced water spatially (i.e., northeast versus southwest Pennsylvania). We then investigated whether ML algorithms applied to a suite of geochemical concentration data (i.e. Ba, Br, Cl, K, Mg, Sr) may be used to predict the lithium concentration of an unknown sample. Finally, we applied an estimated economic lithium grade cutoff of 150 milligrams per liter (mg/l) and assessed the utility of ML to predict whether a produced water sample would fall above or below the grade cutoff based on the suite of geochemical parameters. Four machine learning algorithms—Random Forest (RF), Gradient Boosting Trees (GBT), Extreme Boosting (XGBoost), and Deep Neural Networks (DNN) were assessed. This study successfully demonstrates that all four machine learning methods can precisely and accurately estimate lithium concentrations and geologic formation classification. The products of this study contribute to the growing body of knowledge aimed at expanding the lithium resource base within the United States.

Alabama, Arkansas, Florida, Georgia, Louisiana, Mi↗

USGS2023

The long shadow of a major disaster: Modeled dynamic impacts of the hypothetical HayWired earthquake on California’s economy

We develop and apply a dynamic economic simulation model to analyze the multi-regional impacts of, and mechanisms of recovery from, a major disaster, the HayWired scenario — a hypothetical Magnitude 7.0 earthquake affecting California’s San Francisco Bay Area. The model integrates loss pathways: capital stock damage, labor supply shocks due to short-term population displacement and longer-run out-migration from damaged areas, and the exacerbating effects of damage to transportation infrastructure capital, as well as various aspects of static and dynamic economic resilience. With input substitution-based static inherent resilience and dynamic resilience in the form of optimal intertemporal and spatial investment allocation, gross output losses range from 0.5 percent to 6 percent across regions, and welfare losses are 0.4 percent statewide but can be ten times as large in hardest-hit areas. Large-scale reconstruction investment is supported by substantial interregional transfers of resources through intra-state trade. Increased output via firms engaging in the key adaptive resilience tactic of production recapture can alleviate a substantial fraction of losses—but only if upstream and downstream barriers to recovery can be lowered quickly.

California↗

USGS1993

Small fields in the National Oil and Gas Assessment

In the 1989 National Oil and Gas Assessment prepared by the U.S. Geological Survey (USGS) and the Minerals Management Service, undiscovered oil and gas resources in small fields were assessed separately from resources in fields containing more than 1 million bbl of oil equivalent. This paper concerns the USGS Part of the study: onshore and state waters in the conterminous United States. After the resources in small fields were assessed by geologists, statistical techniques were used to allocate these resources to field-size distributions at the province level. The total numbers of small fields remaining to be discovered is estimated at about 77,800. They account for about 10.6 billion bbl of oil equivalent or 20% of the undiscovered resources in the conterminous United st tes. When an economic analysis was applied to the small fields, none of the offshore small fields were estimated to be commercially developable. For the onshore study area, about 52% of the small oil fields and 46% of the small gas fields are commercially developable. Overall, because more hydrocarbons are contained in the larger size classes of the small fields, about 70% of the undiscovered resources in small fields is expected to be commercially developable.

American Association of Petroleum Geologists Bulle↗

USGS2004

Stable isotopic constraints on fluid-rock interaction and Cu-PGE-S redistribution in the Sonju Lake intrusion, Minnesota

The Sonju Lake intrusion, part of the 1.1 Ga Midcontinent rift-related Beaver Bay Complex, is a 1,200-m-thick, strongly differentiated, layered sequence of mafic cumulates located in northeastern Minnesota. Basal melatroctolite and dunite layers are overlain by troctolite, gabbro, Fe-Ti oxide-rich gabbro, apatite diorite, and monzodiorite. Stratigraphic intervals rich in Pt + Pd, Cu, and S occur over ???500 m in the Fe-Ti oxide-rich gabbro and apatite diorite units. Peak concentrations show offsets that are similar to those found in other tholeiitic layered intrusions. Concentrations of Pd in excess of 100 ppb are confined to the lowermost 25 m of the interval. Copper shows a sharp increase to 630 ppm above the Pd-rich interval. Sulfur contents are low (<375 ppm) in the Cu-rich interval, but they increase to values as high as 3,150 ppm above in the apatite diorite. Disseminated sulfides in the intrusion have ??34S values that range from -2.2 to 3 per mil Vienna-Canyon Diablo Troilite (V-CDT) and suggest that contamination by country rock sulfur was not an important process in the formation of the metal-rich interval. ??18O values of plagioclase from the intrusion range from 5.6 to 12.0 per mil (V-SMOW) and indicate that a relatively low-18O fluid (??18O ???3-5 ???) interacted with the rocks of the intrusion at temperatures less than ???275??C. Clinopyroxene and Fe-Ti oxides (ilmenite with minor amounts of titanomagnetite) show much more restricted ranges in ??18O values (4.6-5.7 and 5.5-6.7 per mil, respectively) and attest to the kinetic control of the oxygen isotope exchange process. The externally derived fluid that interacted with rocks now enriched in platinum group elements (PGE) + Cu- and Fe-sulfide minerals locally liberated sulfur and replaced chalcopyrite and pyrite with goethite. In the Cu-rich zone, goethite that replaces chalcopyrite may contain up to 8.5 weight percent Cu. It is evident that hydrothermal alteration resulted in a decoupling of copper and sulfur, with sulfur being transferred out of the Cu-rich interval. Interaction between rocks in the PGE-Cu-S interval of the Sonju Lake intrusion and an externally derived fluid at low temperatures modified what appears to have been a primary stratigraphic metal-sulfur zonation. The effects of hydrothermal alteration on PGE and base-metal sulfide mobility and redistribution must be understood before models of primary zonation processes can be meaningfully applied. ?? 2004 by Economic Geology.

Economic Geology↗

USGS2022

Valuing angling on reservoirs using benefit transfer

Economic assessments are rarely applied to inland recreational fisheries for management purposes, especially when compared to fish, habitat, and creel assessments, yet economic assessments can provide critical information for management decisions. We provide a brief overview of economic value, key terminology, and existing economic techniques to address these issues. Benefit transfer, a technique used to measure economic value when an original analysis is not practicable, is conducted by drawing on existing estimates of economic value in similar contexts. We describe an application of benefit transfer to measure the economic value of several recreational fisheries in Nebraska, USA. We examine two approaches to benefit transfer—value transfer and function transfer—which we demonstrate estimate similar economic values for fishing site access but substantially different economic values for catch rate improvements at some reservoirs. We encourage agencies that are responsible for inland recreational fisheries management to consider economic assessment, especially benefit transfer, as a critical tool in the management toolbox.

North American Journal of Fisheries Management↗

USGS1993

Economics and the national oil and gas assessment: The case of onshore northern Alaska

The National Oil and Gas Assessment of undiscovered recoverable conventional oil and gas resources assigned nearly 36% of the undiscovered U.S. onshore oil resources and 28% of the commercially developable undiscovered oil resources to onshore northern Alaska. Economic screening models were applied to the geologic play assessment to estimate the commercially developable resources. This paper presents the geologic and economic assessment methodology and results; it also focuses on the robustness of estimates of the commercially developable onshore resources to changes in economic assumptions. With the economic assumptions used in the national assessment, about 60% or 6.49 billion bbl of oil of the recoverable undiscovered resources of 10.76 billion bbl of oil assessed in fields larger than 1 million bbl of oil are estimated to be commercially developable. Changes in facilities costs induced the most significant cost-related response in the commercially developable resource estimates. Price increases or cost reductions that reduce the minimum commercially developable field size to 250 million bbl from the base case size of 380 million bbl added 1 billion bbl of oil to the commercially developable resources. If, through facilities sharing or satellite-field development, the minimum commercial field size is reduced to just below 100 million bbl, estimated developable oil woul increase to 9.17 billion bbl of oil or more than 85% of the assessed recoverable oil in onshore plays.

Alaska↗