The impact of weather and ocean forecasting on hydrocarbon production and pollution management in the Gulf of Mexico

Over the past 2 years, the vulnerability of offshore production in the Gulf of Mexico (GOM) has been brought to light by extensive damage to oil and gas facilities and pipelines resulting from Hurricanes Ivan, Katrina, and Rita. The occurrences of extreme weather regularly force operators to shut-down production, cease drilling and construction activities, and evacuate personnel. Loop currents and eddies can also impact offshore operations and delay installation and drilling activities and reduce the effectiveness of oil spill response strategies. The purpose of this paper is to describe how weather and ocean forecasting impact production activities and pollution management in the GOM. Physical outcome and decision models in support of production and development activities and oil spill response management are presented, and the expected economic benefits that may result from the implementation of an integrated ocean observation network in the region are summarized. Improved ocean observation systems are expected to reduce the uncertainty of forecasting and to enhance the value of ocean/weather information throughout the Gulf region. The source of benefits and the size of activity from which improved ocean observation benefits may be derived are estimated for energy development and production activities and oil spill response management.     

Forecasting risks of natural gas consumption in Slovenia

Efficient operation of modern energy distribution systems often requires forecasting future energy demand. This paper proposes a strategy to estimate forecasting risk. The objective of the proposed method is to improve knowledge about expected forecasting risk and to estimate the expected cash flow in advance, based on the risk model. The strategy combines an energy demand forecasting model, an economic incentive model and a risk model. Basic guidelines are given for the construction of a forecasting model that combines past energy consumption data, weather data and weather forecast. The forecasting model is required to estimate expected forecasting errors that are the basis for forecasting risk estimation. The risk estimation strategy also requires an economic incentive model that describes the influence of forecasting accuracy on the energy distribution systems’ cash flow. The economic model defines the critical forecasting error levels that most strongly influence cash flow. Based on the forecasting model and the economic model, the development of a risk model is proposed. The risk model is associated with critical forecasting error levels in the context of various influential parameters such as seasonal data, month, day of the week and temperature. The risk model is applicable to estimating the daily forecasting risk based on the influential parameters. The proposed approach is illustrated by a case study of a Slovenian natural gas distribution company.     

The impact of Hurricanes Gustav and Ike on offshore oil and gas production in the Gulf of Mexico

During August and September 2008, Hurricanes Gustav and Ike passed through the Gulf of Mexico and damaged and destroyed a number of offshore oil and gas structures. In the final official government assessment, a total of 60 platforms were destroyed and 31 structures were identified as having extensive damage. The destroyed platforms were responsible for about 1.6% of the oil and 2.5% of the gas produced daily in the Gulf of Mexico and represented approximately 234 million BOE of reserves valued between $4.6 and $10.9 billion. Although the number of structures destroyed by Hurricanes Gustav and Ike was half the total destruction from the 2004–2005 hurricane seasons, we estimate that the reserves at risk are approximately three times more valuable. Each destroyed structure is unique in its production capacity and damages incurred and are a candidate for redevelopment. We review pre-hurricane production and revenue characteristics for the collection of destroyed structures and estimate production at risk. Gas structures are expected to present better economics and redevelopment potential than oil structures, and we predict that 198 million BOE, or nearly 95% of reserves-in-place, are likely to be redeveloped. Shut-in production statistics are compared against recent hurricane events and general comments on the factors involved in decision making are presented.     

Modeling lost production from destroyed platforms in the 2004–2005 Gulf of Mexico hurricane seasons

Hurricanes Ivan, Katrina, and Rita passed through the Gulf of Mexico during 2004 and 2005 and resulted in the largest number of destroyed and damaged offshore oil and gas structures in the history of Gulf operations. In the final official government assessment, a total of 126 platforms were destroyed and over 183 structures were identified as having extensive damage. Production associated with wells and structures that are not redeveloped are classified as lost. The purpose of this paper is to derive functional relations that describe the likely contribution the collection of destroyed assets would have made to future production in the Gulf of Mexico. We estimate that the total remaining reserves from the set of destroyed structures range in value between $1.3 and $4.5 billion depending on the assumptions employed. We summarize the impact of the storms on the Gulf of Mexico oil and gas infrastructure and discuss the main issues involved in redevelopment decision making. A meta-model analytic framework is applied to perform sensitivity analysis and to explore the interactions of assumptions on model output. A discussion of the limitations of the analysis is presented.     

Competitiveness of shallow water hydrocarbon development projects in Mexico after 2015 actualization of fiscal reforms: Economic benchmark of new production sharing agreement versus typical U.S. federal lease terms

Development of Mexican hydrocarbon reservoirs by foreign operators has become possible under Mexico's new Hydrocarbon Law, effective as per January 2015. Our study compares the economic returns of shallow water fields in the Gulf of Mexico applying the royalty and taxes due under the fiscal regimes of the U.S. and Mexico. The net present value (NPV) of the base case scenario is US$1.4 billion, assuming standard development and production cost (opex, capex), 10% discount rate accounting for the cost of capital and revenues computed using a reference oil price of $75/bbl. The impact on NPV of oil price volatility is accounted for in a sensitivity analysis. The split of the NPV of shallow water hydrocarbon assets between the two contractual parties, contractor and government, in Mexico and the U.S. is hugely different. Our base case shows that for similar field assets, Mexico's production sharing agreement allocates about $1,150 million to the government and $191 million to the contractor, while under U.S. license conditions the government take is about $700 million and contractor take is $553 million. The current production sharing agreement leaves some marginal shallow water fields in Mexico undeveloped for reasons detailed and quantified in our study.     

An integrated systems framework for service vessel forecasting in the Gulf of Mexico

Throughout the world wherever oil and gas is discovered, a support industry will develop and evolve with the needs of industry and government regulation. In the Gulf of Mexico, a large variety of marine vessels transport goods and provide services to exploration, development and production activity, and play an important role in the economic and ecological impacts across communities. The spatial and temporal dynamics of the logistics network is complex and dynamic and closely related to the magnitude, duration, type, and sequence of offshore workflows and activities. The purpose of this paper is to develop a methodological framework to quantify the number of offshore supply vessel and crew boat departures by activity across the Gulf’s coastal regions in support of the oil and gas industry. The logistics network is modeled as a linear time-invariant deterministic system and implemented using an input-output model. We provide a methodological framework to quantify the magnitude and distribution of service vessel trips to forecast port activity. This is the first integrated modeling study on service vessel trips in the Gulf of Mexico and special attention is paid to the analytic framework, model assumptions, and limitations of the analysis. Generic examples illustrate the model implementation.     

Wind speed forecasting in the South Coast of Oaxaca, México

Comparison of two techniques for wind speed forecasting in the South Coast of the state of Oaxaca, Mexico is presented in this paper. The Autoregressive Integrated Moving Average (ARIMA) and the Artificial Neural Networks (ANN) methods are applied to a time series conformed by 7 years of wind speed measurements. Six years were used in the formulation of the models and the last year was used to validate and compare the effectiveness of the generated prediction by the techniques mentioned above. Seasonal ARIMA models present a better sensitivity to the adjustment and prediction of the wind speed for this case in particular. Nevertheless, it was shown both developed models can be used to predict in a reasonable way, the monthly electricity production of the wind power stations in La Venta, Oaxaca, Mexico to support the operators of the Electric Utility Control Centre.     

Forecasting ramps of wind power production with numerical weather prediction ensembles

Today, there is a growing interest in developing short‐term wind power forecasting tools able to provide reliable information about particular, so‐called ‘extreme’ situations. One of them is the large and sharp variation of the production a wind farm can experience within a few hours called ramp event. Developing forecast information specially dedicated to ramps is of primary interest because of both the difficulties that usual models have to predict and the potential risk they represent in the management of a power system. First, we propose a methodology to characterize ramps of wind power production with a derivative filtering approach derived from the edge detection literature. Then we investigate the skill of numerical weather prediction ensembles to make probabilistic forecasts of ramp occurrence. Through conditioning probability forecasts of ramp occurrence to the number of ensemble members forecasting a ramp in time intervals, we show how ensembles can be used to provide reliable forecasts of ramps with sharpness. Our study relies on 18 months of wind power measures from an 8 MW wind farm located in France and forecasts ensemble of 51 members from the Ensemble Prediction System of the European Center for Medium‐Range Weather Forecasts. Copyright © 2012 John Wiley & Sons, Ltd.     

Online 24-h solar power forecasting based on weather type classification using artificial neural network

Power forecasting is an important factor for planning the operations of photovoltaic (PV) system. This paper presents an advanced statistical method for solar power forecasting based on artificial intelligence techniques. The method requires as input past power measurements and meteorological forecasts of solar irradiance, relative humidity and temperature at the site of the photovoltaic power system. A self-organized map (SOM) is trained to classify the local weather type of 24 h ahead provided by the online meteorological services. A unique feature of the method is that following a preliminary weather type classification, the neural networks can be well trained to improve the forecast accuracy. The proposed method is suitable for operational planning of transmission system operator, i.e. forecasting horizon of 24 h ahead and for PV power system operators trading in electricity markets. Application of the forecasting method on the power production of an actual PV power system shows the validity of the method.     

Fiscal system analysis—concessionary systems

The economic and system measures associated with hydrocarbon development are subject to various levels of private and market uncertainty. The purpose of this paper is to develop an analytic framework to quantify the influence of private and market uncertainty under a concessionary fiscal system. A meta-modeling approach is employed to develop regression models for take and investment criteria in terms of various exogenous, fiscal, and user-defined parameters. The critical assumptions involved in estimation, the uncertainty associated with interpretation, and the limitations of the analysis are examined. The deepwater Gulf of Mexico Na Kika development is considered as a case study.     

Hydrocarbon production forecast for committed assets in the shallow water Outer Continental Shelf of the Gulf of Mexico

In 2007, the federal waters of the Gulf of Mexico averaged daily production of 1.3 million barrels of oil and 7.6 billion cubic feet of natural gas. The majority of oil is produced from deepwater fields in water depth greater than 1000 ft, while most gas production is extracted from the shelf. The Outer Continental Shelf is a mature province with over 3800 fixed structures and 6500 producing wells connected into an integrated pipeline network more than 30,000 miles in length. The purpose of this paper is to develop a methodology to forecast oil and gas production in the shallow water Gulf of Mexico. Structures are categorized according to age and production characteristics, and forecast procedures for each asset class are described and illustrated. The methodology is implemented using the inventory of committed assets circa December 2006. The expected amount of hydrocarbon production arising from the inventory of committed assets under stable reservoir and investment conditions is estimated to be 1056 MMbbl oil and 13.3 Tcf gas valued between $85 and 150 billion. The results of generalized regression models are presented with a discussion of the limitations of analysis.     

Economic limit of Outer Continental Shelf Gulf of Mexico structure production

The economic limit of an oil and gas asset occurs when income from production is less than the direct cost of operation. Economic limits determine the threshold for profitable operations and are often considered from a conceptual perspective rather than as an object for empirical assessment. The purpose of this paper is to derive empirical estimates of the economic limit of offshore structures in the Outer Continental Shelf Gulf of Mexico. We classify 1962 decommissioned structures between 1986–2009 by structure type, primary production, water depth and year of removal, and compute end-of-life production, adjusted gross revenue, and water cut thresholds according to various levels of categorization. During the last year of production, historic gross revenues averaged $539,000 for oil structures, $955,000 for gas structures, and $1.1 million for dry gas structures. Daily end-of-life production ranged from 50 BOEPD for oil structures to 647 MCFEPD for gas structures and 788 MCFEPD for dry gas structures. The economic limits for oil and gas structures increased to $1 million and $1.7 million over the period 2005–2009.     

Feasibility assessment of wind energy resources in Malaysia based on NWP models

There is a common belief that countries located in the doldrums with prevailing monotonous weather, characterized by light winds, cannot harness the wind for feasible energy production. This paper reexamines such a belief and presents a novel approach to assess the techno-economic potential of wind turbine generator sites in Malaysia, which lies in the equatorial, low wind speed doldrums. Dissimilar to other techniques that account for planetary-scale winds only, a numerical weather prediction (NWP) prospecting tool for mesoscale winds is used to forecast the wind characteristics. Potential sites from the forecasting studies are further investigated for economic feasibility by using a commercial wind turbine generator and a financial analysis method. From the economic analysis, it is found that unlike what is widely touted, there is an actual potential of wind energy in Malaysia, manifested through the several economically viable wind turbine generating sites.     

基于改进的SCS模型的城市径流预测系统研究

鉴于城市的发展引起下垫面变化,进而对城市径流产生一定影响,利用改进的SCS模型,根据历史降雨径流资料率定得到了城市现状CN值;以城市规划为依据,计算了CN值的变化,预测了土地利用方式的改变对径流的直接影响;利用Matlab建立了城市径流预测系统,并将其应用于济南市小清河流域,预测了1990～2005年径流过程的改变情况。结果表明,该预测系统有效、合理,在城市规划时可为决策者提供较合理的土地利用方式,从而避免不合理的下垫面变化,以降低洪水的灾害性。