Modellverktøy. Mathijs Smit, Principle researcher, Miljøteknologi Statoil R&D

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1 Modellverktøy Mathijs Smit, Principle researcher, Miljøteknologi Statoil R&D OG21 Olje og Gass i det 21. århundre Norges teknologistrategi for petroleumsindustrien

2 Message Modelling tools e.g. for risk assessment, are applied in O&G environmental management systems Guidelines and tools for regulatory risk assessment have limitations in the context of Ecosystem-Based Management Ecosystem-Based Management requires ecosystem knowledge and models being integrated in risk assessment frameworks Ecological models provide structure and focus for R&D efforts and enhance ecosystem understanding There is a need for integrated modeling frameworks that support ecosystem-based management of the Arctic

3 Environmental management system to meet the zero harm objective

4 Environmental risk assessment and monitoring Monitoring Impacts / Document zero harm

5 Exposure modeling Proper assessment of contaminant concentrations in the environment is crucial for reliable risk assessment From simple plume models to sophisticated 3-D dispersion models Important input: Hydrodynamics, winds, currents, bathymetry Existing exposure models need to be parameterised and validated for frontier areas

6 6 Risk assessment: a stepwise process From risk screening to realistic impact assessment Level 1: worst-case exposure versus most senstive species Level 2: distributions of exposure and sensitivity Level 3: biology-based assessments Level 1: If the objective is to reduce risks (e.g. EIF for produced water) Absolute quantification is not required. Relative risk is used to define priorities Level 3: Quantification of risks (most likely impacts and uncertainty estimates) To support go/no-go decisions Compare results with accepted risk/impact levels Compare results in an integrated assessment with other activities

7 EIF: Example of a risk screening model PEC Concentration field EIF groups BTEX Naphthalenes PAH 2-3 ring PAH 4+ ring Alkyl phenols C0-C3 Alkyl phenols C4-C5 Alkyl phenols C6-C9 Dispersed oil Copper Zinc Nickel Lead Cadmium Mercury Added chemicals Pie charts - contibution to EIF Risk expressed as PEC/PNEC

8 Example of use of EIF PW as risk management tool Snorre A/Vigdis More than 90% reduction in EIF over the period 2002 to 2008 EIF Epcon installed; Discharge of biocides reduced; Application of H 2 S scavanger optimised. New H 2 S scavanger New Epcon installed Improved separation Year Smit et al., Achievements of risk-based produced water management on the Norwegian continental shelf ( ) Integr. Environ. Assess. Manag. 7: (link)

9 Achievements using EIF PW for NCS ( ) Summed EIF PW for all installations on the NCS is reduced by 55% over the period 2002 to 2008, despite an increase of discharge volumes in the same period EIF Summed EIF PW for all Statoil operated installations on the NCS Sum EIF Year Volume PW discharged (10 6 m 3) SUM EIF

10 10

11 11 Integrated Management Management of all human activities All potential impacts should be compared and summed to ass the overall environmental consequences Challenge: Potential impacts from future developments (e.g. oil and gas, climate change) must be compared to empirical data of reported and known impacts from other activities (e.g. fisheries ) The best alternative is to assess potential future impacts based on best available knowledge and quantitative impact models

12 (Mis)use of risk screening models hampers knowledge-based decision making

13 Ecosystem-based management requires ecosystem knowledge being applied in Risk Assessment - SYMBIOSES > 68 North Cod Capelin zooplankton phytoplankton

14 Ecosystem-based management requires ecosystem knowledge being applied in Risk Assessment Identification of important ecological resources Water column seabirds marine mammals bentic communities Basic ecological knowledge (populations, communities, foodwebs) combined with information on stressor response functions Seismic drilling production accidents spatial planning

15 Need for assessment tools that support ecosystem-based management of the Arctic Integrated modelling systems that allow for the calculation of potential impacts of petroleum activities on important ecologcal resources Based on available knowledge, models and data Provides a possibility for hypoteses testing Multi scenario testing (time, location, discharge) Realistic risk picture most likely value and uncertainty Ecosystem modeling provides a framework that enhances ecosystem understanding and helps to focus on the main environmental challenges in sensitive areas International consortia Common understanding of the main challanges Focused research agenda

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