Sources of data used in the Energy Export Databrowser

This page describes the data sources used in the
Energy Export Databrowser.
You may show or hide any section by clicking on the section header.

BP Statistical Review 2017

The BP Statistical Review is British Petroleum's best effort to review world energy trends. Produced once a year,
the Excel workbook
contains regional consumption and production data for Oil, Natural Gas, Coal, Nuclear and Hydroelectric energy resources.
Data from several worksheets in the Statistical Review are used as input to the Energy Export Databrowser.
The data used by the Databrowser are unaltered except
for minor cleanup as described the section on "ISO Standardized Data" below.
It is assumed that BP has made every effort to harmonize data from different sources and ensure that values within this
workbook are consistent and comparable between nations.

Definitions

All definitions are taken verbatim from the BP Statistical Review worksheets.

Includes crude oil, shale oil, oil sands and NGLs (the liquid content of natural gas where this is recovered separately).

Oil Consumption

Inland demand plus international aviation and marine bunkers and refinery fuel and loss. Consumption of
fuel ethanol and biodiesel is also included.

Natural Gas Production

Excludes gas flared or recycled. As data are derived from tonnes oil equivalent using average conversion factors, they
do not necessarily equate with gas volumes expressed in specific national terms.

Natural Gas Consumption

Differences between consumption figures and production statistics are due to variations in stocks at storage
facilities and liquefaction plants, together with unavoidable disparities in the definition, measurement or conversion
of gas supply and demand data. As data are derived from tonnes oil equivalent using average conversion factors, they
do not necessarily equate with gas volumes expressed in specific national terms.

Hydro Production

Based on gross primary hydroelectric generation and not accounting for cross-border electricity supply.

Hydro Consumption

Based on gross primary hydroelectric generation and not accounting for cross-border electricity supply.

Nuclear Production

Based on gross generation and not accounting for cross-border electricity supply.

Nuclear Consumption

Based on gross generation and not accounting for cross-border electricity supply.

Notes

The "Definitions" worksheet of the Statistical review contains the following note:

The primary energy values of both nuclear and hydroelectric power generation have
been derived by calculating the equivalent amount of fossil fuel required to generate
the same volume of electricity in a thermal power station, assuming a conversion
efficiency of 38% (the average for OECD thermal power generation).

This means that the data in the nuclear and hydroelectric worksheets in units of 'mtoe' (milltion tonnes of oil equivalent) are scaled
up by a factor of 1/0.38 (=2.63).
When fossil fuels are used primarily for generation of electricty, this scaling can be useful.
It allows the amount of electrical energy available to consumers from nuclear and hydro power plants to be compared with the amount
available to consumers from coal/oil/gas fired power plants.

To see the unscaled energy produced by nuclear and hydro power plants you must choose units of
'twh' (Terawatt-hours) or 'J' (Exajoules). Choosing units of Exajoules allows one to compare energy generated from nuclear or
hydro with the 'embedded energy' in fossil fuels. From the standpoint of energy avaiable for human use, without assumptions
as to how it will be used, Exajoules is a more appropriate unit.

Original Data

The original 2017 Statistical Review may be obtained from British Petroleum:

ISO Standardized Data

For use in the Energy Export Databrowser, these data were converted from Excel spreadsheets with English
language country names into ASCII CSV files with
ISO 3166-1
two-digit country codes. These standardized data files are offered to the community in the interest of
promoting internationalization and further investigation of the data.

Additional cleanup of the Excel worksheets included:

conversion of numeric values stored as characters into floating point values

conversion of '^' and '-' markers into floating point 0.0

conversion of 'n/a' missing values markers to 'na'

conversion of regions with no country equivalent into unique codes of the form: "BP_~~~" (e.g.Total North America = BP_TNA)