The CD-ROM contains the input/output, on a regional basis, for the study’s principal modeling activities, as well as the digitized maps that were used in assessing the potential impact of conditions of approval for access to key Rocky Mountain resource areas. It also contains digital copies of the NPC’s five-volume report, and a copy of the presentation made to the NPC at its meeting on September 25, 2003.
The following provides a detailed description of the NPC's Natural Gas study approach, as well as the Modeling Activities contained in this CD.
To order this CD-ROM, download and return this 2003 Natural Gas Report order form.
The NPC developed two scenarios of future supply and demand that move beyond the status quo. Both require significant actions by policy makers and industry stakeholders to effect change.
Each of the two scenarios has different assumptions regarding key variables related to supply and demand in response to public policy choices. These key variables included degrees of access to gas resources, greater energy efficiency and conservation, and increased flexibility to use fuels other than gas for industry and power generation. The two scenarios result in contrasting demand, supply, infrastructure, and price profiles. Each scenario assumes a continuation of current standards for environmental compliance.
The “Reactive Path” scenario assumes continued conflict between natural gas supply and demand policies that support natural gas use, but tend to discourage supply development. However, in addition to these broad policies, the assumptions built into this case acknowledge that resultant higher natural gas prices will likely be reflected in significant societal pressure to allow reasonable, economically driven choices to occur on both the consuming and producing segments of the natural gas industry. In essence, market participants, including public policy makers, “react” to the current situation while inherent conflicts continue. The supply response assumes a considerable amount of success and deviation from past trends, evidenced by a major expansion of LNG facilities, construction of Arctic pipelines, and a significant response in lower-48 production from accessible areas. The resulting demand level is lower than other outlooks including the EIA, with less upward pressure on the supply-demand balance. Even with uncertainty surrounding air quality regulations, there is potential for construction of new, state of the art, fully compliant coal-based generation plants at levels that approach the prior coal boom years in the 1970s. Together, this scenario implies a degree of success in supply and demand responses significantly beyond what has been demonstrated over recent years.
Reactive Path Scenario
Alternatively, “Balanced Future” is a scenario in which government policies are focused on eliminating barriers to market efficiencies. This scenario enables natural gas markets to develop in a manner in which improved economic and environmental choices can be made by both producers and consumers. On the demand side, opportunities for conservation, energy efficiency, and fuel flexibility are both authorized and encouraged while adhering to current environmental standards. On the supply side, barriers to development of new natural gas sources are progressively lowered, both for domestic and imported natural gas. The result is a market with lower gas prices and volatility due to enhanced supply and more flexible demand. This scenario results in a better outcome for North American consumers than the “Reactive Path”.
Balanced Future Scenario
As in the 1992 and 1999 studies, econometric models of North American energy markets and other analytical tools were used to support the analyses. Significant computer modeling and data support were obtained from outside contractors; and an internal NPC study modeling team was established to take direct responsibility for some of the modeling work. The Coordinating Subcommittee and its Task Groups made all decisions on model input data and assumptions, directed or implemented appropriate modifications to model architecture, and reviewed all output. Energy and Environmental Analysis, Inc. (EEA) of Arlington, Virginia, supplied the principal energy market models used in this study, and supplemental analyses were conducted with models from Altos Management of Los Altos, California.
The use of these models was designed to give quantified estimates of potential outcomes of natural gas demand, supply, price and investment over the study time horizon, with a particular emphasis on illustrating the impacts of policy choices on natural gas markets. The results produced by the models are critically dependent on many factors, including the structure and architecture of the models, the level of detail of the markets portrayed in the models, the mathematical algorithms used, and the input assumptions specified by the NPC Study Task Groups. As such, the results produced by the models and portrayed in the NPC report should not be viewed as forecasts or as precise point estimates of any future level of supply, demand, or price. Rather, they should be used as indicators of trends and ranges of likely outcomes stemming from the particular assumptions made. In particular, the model results are indicative of the likely directional impacts of pursuing particular public policy choices relative to North American natural gas markets. (Further model information is available in the Integrated Report and the Task Group Reports.)
The NPC Cases
In addition to the Reactive Path and Balanced Future Scenario, a series of sensitivity cases were also constructed. This figure shows in a summary fashion how the 32 main cases were constructed. Each row on the figure represents a separate case and each column represents a category of assumptions that could be changed among the cases. The assumptions are shown in the figure as changes relative to the Reactive Path case. Therefore, when assumptions are the same as the Reactive Path case, that will be indicated as a blank box in the figure.
The Balanced Future scenario is presented in this report as the primary alternative to the Reactive Path scenario. As is shown in the second row of the figure, the Balanced Future scenario contains different assumptions:
Some of these same assumptions were used in other cases. For example, the case appearing in row 24 is the Fuel Flexibility case. It contains all of the same assumptions as the Balanced Future Case, with the exception of land access, which is kept the same as in the Reactive Path case. Row 25 contains the LNG Stress Test case, which has the same assumptions as the Balanced Future with the exceptions of higher LNG imports.
Most of the sensitivity cases appearing in this report were run off of the Reactive Path case. For example, rows 3 and 4 show the GDP sensitivities, which contain the same assumptions as the Reactive Path case for everything but the economic environment. The same pattern of change in only one column appears for:
Two other scenarios were also created and are shown in rows 30 and 31.
The Carbon Reduction scenario contained limitations of carbon emissions from power plants that were met by reduced use of coal and more use of natural gas and nuclear power. The Status Quo scenario represented what might happen if some of the regulatory hurdles to additional gas supplies and alternative fuel use were not eased even to the degree anticipated in the Reactive Path scenario. This was represented in the EEA models as the combined effect of decreased access to land, no Alaska natural gas pipeline, low LNG imports and delayed construction of coal power plants. Because of the high natural gas and electricity prices produced in this case, expected feedback effects of reduced electricity consumption and more renewables use were also made part of the Status Quo scenario.
In addition to the cases represented, EEA also ran a large number of weather sensitivity cases off of the Reactive Path and Balanced Future scenarios. This was done by changing the heating degree days and cooling degree days by region and month in various future years. The purpose of these weather cases was to measure the degree of stress on the natural gas transmission and storage infrastructure caused by extreme weather and how natural gas price levels and volatility are affected.
This section describes the natural gas market modeling methodologies used by the NPC. The modeling framework developed and maintained by Energy and Environmental Analysis, Inc. (EEA) formed the basis of gas market outlooks in the current study. Additional work was conducted to apply data and develop underlying assumptions for models by Altos Management Partners so that these models could be considered for application in future NPC efforts, as well as to make NPC information more readily available to a wider group of users.
In the course of this study, the NPC developed databases related to resource base quantities and production costs, gas pipeline capacity and rates, and characterizations of gas demand volumes versus price. It is the intent of the NPC to make these data available to government agencies and other interested parties. The NPC also will continue working with government agencies, such as the USGS, to determine the feasibility of updating, utilizing, and maintaining the resource, engineering, and cost data developed by the NPC.
Resource Assessment Data
The NPC study's resource assessment was based on best practices learned from prior NPC studies and from other similar studies. It was designed to use publicly available data, to be play-based, and to provide a thorough review by geoscientists and engineers. The resulting assessment represents an industry consensus.
Many sources of public and commercial data were used. For the United States, data from the Minerals Management Service (MMS) and United States Geological Survey (USGS) comprised the baseline data. For Canada, the Canadian Gas Potential Committee (CGPC) assessment was primarily used. For Mexico, a combination of IHS Energy Group (IHS) and USGS data were used. Production performance data were derived from the Energy Information Administration (EIA), IHS, and NRG Associates (Nehring). Cost data were derived from the American Petroleum Institute (API) in the United States and the Petroleum Services Association of Canada (PSAC) in Canada.
A critical part of the NPC study was estimating reasonable costs for use in the model to determine commercial resources. Costs were needed for all aspects of onshore and offshore gas development exploration and development drilling, production and lease facilities, and operations and maintenance. Where possible, public and commercial databases were used to estimate costs. Sources included, among others, the API Joint Association Survey on Drilling Costs, the PSAC Well Cost Studies, and the EIA Oil & Gas Lease Equipment and Operating Costs report. In areas where adequate public and commercial data were not available, costs were based on available information and circulated for review and comment to industry experts familiar with costs in that area. Costs were then revised based on the input received. At each of the regional workshops, which were held primarily to review the resources, costs were also discussed in order to determine the key factors that might affect costs in that region (i.e., infrastructure, weather, drilling depths, etc.).
The costs used in the model are average costs for generic operations. For example, the well costs are for generic wells at an average drill depth. Actual costs will vary with regards to water depth, drill depth, pore pressure, rig type, etc., depending on specific locations. The same is true for development costs. Actual costs will depend on location, infrastructure, metocean conditions, well productivity, etc. All costs used in the modeling exercise were expressed in year 2000 dollars.
Resource Access Data
The NPC access analysis studied a limited number of the lower-48 basins that were reviewed in the resource assessment portion of the study. The access analysis focused on those basins with large remaining potential and with significant access constraints. These basins are located in the Rocky Mountain region of the United States (Green River, Uinta/Piceance, Powder River, San Juan, Wyoming Thrust Belt) and offshore Atlantic, Pacific, and Eastern Gulf of Mexico.
The analysis focused on post leasing conditions of approval. The term “conditions of approval” (COA) refers to development requirements that arise during the permitting process that takes place after leases are obtained. These COAs are governed by several controlling authorities, but the most significant and wide-ranging tend to be those based on federal legislation concerning environmental policy, species protection, and historic preservation.
The NPC developed extensive maps showing the surface areas subject to COA issues. To perform this mapping, NPC contracted with Hayden-Wing and Associates, an environmental consulting firm located in Laramie, Wyoming. Hayden-Wing is widely recognized for its expertise in wildlife surveys, environmental impact statements, wetland evaluations, and developmental permitting. In addition to the preparation of these maps, Hayden-Wing quantified the percentage of the land areas in these basins that are covered by each habitat and migratory range. They also estimated the frequency of occurrences requiring specific survey or mitigation actions on the part of oil and gas operators, such as active raptor nests, active Sage Grouse leks, big game birthing habitats, and other similar circumstances.
The NPC estimated the cost and time delay caused by the COAs related to the species occurrences described above, as well as for archaeological activities governed by the National Historic Preservation Act and for environmental analyses and environmental impact statements required by the National Environmental Policy Act (NEPA). These data were developed by analyzing costs and delays incurred on actual projects conducted in these basins. The NPC also determined whether each COA also applied to state and fee lands, in addition to federal lands. Once all of the data had been compiled, they were analyzed with the help of a probability analysis program created by EEA specifically for this project.
The study also examined the issue of access in Canada, and, referencing the recently published study on Potential Canadian Gas Supply (conducted by the Canadian Energy Research Institute) estimated the percentages of the various producing basins that are currently off-limits to leasing. These percentages were used in the long-range modeling process. Although there are other access and environmental issues in Canada, generally speaking, access issues in Canada are less significant than in the United States. Therefore, alternative policy cases related to Canadian access restrictions were not conducted and likely would not have had a material impact on the 2003 NPC study.
The EEA Models
Models licensed from Energy and Environmental Analysis, Inc. (EEA) for this study included the Hydrocarbon Supply Model (HSM) and the Gas Market Data and Forecasting System (GMDFS). The HSM models supply on an annual basis, while the GMDFS simulates monthly market behavior, and the models are operated in an integrated manner. The primary inputs from the HSM into GMDFS are gas deliverability data, and the primary data going back from GMDFS to the HSM are gas production levels and prices.
The EEA models solve using a “market simulation” methodology, meaning the decisions are simulated on a period-by-period basis using foresight assumptions set by the user. As such, the EEA models produce results that match history and provide insight into the future natural gas market.
Earlier versions of the HSM were used in both the 1992 and 1999 NPC studies. The GMDFS also was used in the 1999 study. Several changes were made to those models since the 1999 study, both independently by EEA, and in consultation with the NPC. The major changes for the 2003 NPC study, in contrast to earlier studies, include:
Gas Market Data and Forecasting System
The Gas Market Data and Forecasting System has the capability to track and analyze the performance of North American natural gas markets on a monthly basis. At the heart of the system is a comprehensive gas transmission network that solves for natural gas supply and demand in the United States, Canada, and northern Mexico. Specifically, the model solves for monthly natural gas production and demand, storage injections and withdrawals, pipeline flows, natural gas prices, location, and seasonal basis for a very detailed natural gas pipeline network comprised of over 100 nodes (or market hubs). Results are described at the node level. In the power generation sector, the GMDFS solves for monthly U.S. electricity demand, power generation by type of fuel, and fuel use.
The GMDFS model simulates monthly gas market performance to 2030, considering the impact of a wide range of variables. Inputs include: growth rates for economic drivers, such as GDP and industrial production; projected prices of crude oil and alternative fuels; power generating capacity by technology and fuel supply; weather and hydrological conditions; pipeline and storage expansions; LNG imports and exports; and other annual and seasonal factors.
Overall, the model solves for monthly natural gas market clearing prices by considering the interaction between supply and demand relationships at each of the model’s nodes. On the supply side, prices are determined by short-term production and storage price curves that reflect prices as a function of production and storage utilization. Prices are also influenced by “pipeline discount” curves, which reflect the change in basis or the marginal value of gas transmission as a function of load factor. On the demand side, prices are represented by a curve that captures the fuel-switching behavior of end-users at different price levels. The model balances supply and demand at all nodes in the model at the market clearing prices determined by the shape of the supply and demand curves. EEA maintains this model by doing significant “backcasting” (calibration) of the model’s curves and relationships on a monthly basis to make sure that the model reliably reflects historical gas market behavior, instilling confidence in the projected results.
The NPC provided input assumptions for weather, economic growth, and oil prices, among other variables. EEA performs market reconnaissance and keeps the model up to date with generating capacity, near-term gas supply deliverability, storage and pipeline expansions, and the impact of regulatory changes in gas transmission.
Since the GMDFS solves on a monthly basis, EEA’s Daily Demand model was used to determine daily gas demands. The Daily Demand model is an offshoot of the GMDFS. It is based on the same nodal structure and demand modules used by the GMDFS, but runs for each day of a given historical or future year. The output of the Daily Demand model is daily residential, commercial, industrial, and power generation gas demand at each model node, and daily fossil generation for each of the model’s power dispatch regions. The Daily Demand model was used by the NPC to project peak-day demands, assess the need for high-deliverability storage, and identify possible pipeline constraints.
In contrast to the GMDFS, which solves for the full supply and demand balance at each node to arrive at natural gas market clearing prices, the Daily Demand model uses the gas prices from a GMDFS model run to determine daily demand at each node. Once a GMDFS model run is complete, the Daily Demand routine is run using the same inputs as the GMDFS, plus the gas price outputs from the GMDFS model run. The daily temperatures used in the Daily Demand model are adjusted to match the total monthly heating and cooling degree-day values used as input for the GMDFS. This allowed the NPC to model the demand variability within each month and distribute the monthly load over the days of the month.
Hydrocarbon Supply Model
The Hydrocarbon Supply Model is an analytical framework designed for the simulation, forecasting, and analysis of natural gas, crude oil, and natural gas liquids supply and cost trends in the United States and Canada. It is a process-engineering model with a detailed representation of potential gas resources and the technologies with which those resources can be proven and produced. The degree and timing by which resources are proven and produced are determined in the model through discounted cash flow analyses of alternative investment options and behavioral assumptions in the form of inertial and cash flow constraints and the logic for setting producers' market expectations (i.e., future gas prices).
The model covers the U.S. lower-48, Alaska, and Canada. The lower-48 states are represented in 28 onshore regions and 11 offshore regions. Alaska is divided into seven regions, and Canada is divided into ten regions. All regions are further broken out into subregions or “intervals.” Each of these “intervals” represents some combination of drilling depths, water depth, or geographic areas.
Resources in the Hydrocarbon Supply Model are divided into three general categories: new fields/new pools, field appreciation (growth), and nonconventional gas. For conventional resources in the United States, there are 220 region/interval categories that are modeled with over 10,000 prototypical field development plans. Old-field appreciation is modeled in approximately 525 categories. Nonconventional gas is represented by 261 “cells” that, for the United States, correspond to the “continuous plays” of USGS resource assessments.
The Hydrocarbon Supply Model has a large number of factors that can be changed to produce alternative cases. These include:
Exploration, Development, and Production Costs
Model output includes annual forecasted number of wells drilled by type, reserve additions, production, end-of-year reserves, and various cash flow accounts. Outputs can be in viewed in Microsoft Excel and Access format and include details by type of natural gas and by model regions/intervals.