The Oil Questionnaire TARES/IEA Energy Statistics Training Cairo, Oct. 20-23, 2014 Pierre Boileau International Energy Agency OECD/IEA 2010
Presentation overview Introduction Collecting data from different sources Processing data Checking
Share of oil in Total Primary Energy Supply OIL 44% - 1971 37% - 1990 32% - 2011 Oil remains the most important fuel in the world s energy supply
Oil Questionnaire Introduction Collecting data from different sources Processing data Checking
Oil Questionnaire Collecting Reporting Checking
Typical Data Collection Cycle Year-2 Year-1 Year DATA COLLECTION PROCESS DATA DISSEMINATION COUNTRY AFREC OIL AFREC
Collecting data National authority IEA
Oil Questionnaire Introduction Collecting data from different sources Processing data Checking
Oil Questionnaire Structure Supply Transformation Consumption
Crude Oil & Other Non Crude Flow Chart From other sources Exports Stock build IEA: Direct use Production Inland deliveries Refineries Imports Transfers Stock draw
Oil Questionnaire Supply of Crude Oil & Other Non-Crude Table overview Other Non Crude Also includes Feedstock, Additives and Natural gas liquids (NGL) Coal to liquids and Gas to liquids output to be accounted Stock changes = Opening - Closing
Questionnaire Structure Supply Transformation Consumption
Petroleum Products Flow Chart Refinery Fuel International bunkers Exports Stock build Gross output Total supply Refinery Imports Transfers Crude Oil Stock draw
Oil Questionnaire Petroleum Products Table Overview
Oil Questionnaire Petroleum Products 1. LPG Ethane, propane, butane 2. Other products Naphtha, bitumen, lubricants, petroleum coke 3. Jet kerosene Used mainly for domestic aviation and International Aviation Bunkers 4. Other kerosene Used mainly in the residential sector 5. High sulphur fuel oil/low sulphur fuel oil Used mainly as International Marine bunkers, electricity generation, space heating
Oil table details Transformation Refinery, Power generation, GTL, CTL etc. Input in energy units Efficiency = Output / input Output in energy units x NCV x 1 / NCV Input in natural units Refinery losses = Input - output Output in natural units
The Weighted Average How to calculate one value to describe a mixture of substances from different sources: The weighted average! Source 1 Qty 1 NCV 1 Source 2 Qty 2 NCV 2 NCV = NCV 1 *Qty 1 + NCV 2 *Qty 2 + NCV 3 *Qty 3 Qty 1 + Qty 2 + Qty 3 Source 3 Qty 3 NCV 3 The same principle applies to densities or any other feature
Oil Questionnaire Refinery output of petroleum products
Transformation & Energy Sector Refineries producing petroleum products Quantities of fuel that will be use to produce another energy form Electricity production: both main activity and autoproducer All other transformation Quantities of fuel that will be consumed to support the oil and gas extraction or the transformation activity
Questionnaire Structure Supply Transformation Consumption
How are oil products used? Transformation sector Transport sector Total supply Energy sector Distribution losses Total final consumption Industry sector Residential, commercial, agriculture, fishing, etc. Non-energy use
Oil Questionnaire Transformation and Final Consumption
Final Consumption Oil used for international transport, regardless of the sector Breakdown International/domestic aviation is very important for CO 2 calculations Always report negative numbers here Oil used for other economic activities Defined by ISIC codes Agriculture includes non-highway use in tractors Oil products used for nonenergy purposes in any sector Example: raw materials for petrochemical production
Oil Questionnaire Introduction Collecting data from different sources Processing data Checking
Verification of the questionnaire Checks are provided directly in the questionnaire Refinery Losses check Ratio of secondary oil product output and crude oil input Should not be higher than 4% (otherwise considered too inefficient) Should not show gains of secondary products Statistical Difference Difference between supply and consumption Should not be higher than 5%, otherwise data inconsistencies are too high.
Main Quality Problems Timeliness Breaks in time series Statistical Differences Negative Refinery Losses Trade (Inaccurate imports and exports) Inconsistencies between Tables (e.g. oil versus electricity)
kilotonnes Breaks in time series 11000 10500 10000 Crude Oil Production? 9500 9000 8500 8000 7500 7000
Thank you! wed@iea.org