About the Energy Export Databrowser

This page gives advice on using the Energy Export Databrowser and interpreting results. You may show or hide any section by clicking on the section header.


Access to fossil fuels is one of the most important issues of our time. The world's largest economies are extremely dependent upon imported supplies of oil and gas. Understanding who produces and consumes oil, coal and natural gas is critical today and will remain so in the years ahead.

This databrowser uses data from the 2017 BP Statistical Review and displays coal, oil & natural gas production and consumption timelines for each country in the database and several political and geographic groupings of nations. Users can dynamically plot import/export curves to get a sense of who the major fossil fuel producers and consumers are and how this has changed in the last four decades.

More about databrowsers

A databrowser is a web based interface that allows non-technical users to interact with scientific data.

Making sense of complex datasets depends upon two very different kinds of machines. Silicon based number crunchers (computers) perform complex mathematical calculations at lightning speed with essentially zero errors while carbon based pattern recognizers (our brains) detect visual patterns much faster than any computer and use these patterns to develop further questions about the data.

People enjoy looking at informative scientific graphics if the barrier to creating them is low. When this happens, our species' extraordinary capabilities as pattern recognizers enable us to convert what we see in excellent scientific graphics into a deeper understanding. The problem in many fields of science is that the barriers to creating excellent graphics are discouragingly high.

A bottleneck exists where information is transferred between number crunchers and pattern recognizers. It can take a large amount of time to organize, format and analyze data before generating the graphics that tell the story of the data. Often, the role of data management and analysis is handed over to computer experts rather than the scientist end users with a real interest in the data. With no easy way to create the graphics that they need, the ability of scientits, managers and interested members of the public to develop their intuition about a dataset is greatly impaired.

Scientific databrowsers attempt to solve this problem by hiding the details of data management and analysis while providing simple, intuitive interfaces to the kinds of analysis that are appropriate for a particular dataset. These analyses are typically vetted statistical routines that are written in code in such a way as to be driven by input from a web browser user interface. In this manner, end users including both experts and non-experts can harness the power of (server side) number crunchers as well as their own (client side) pattern recognizers without having to learn the arcana of data management and scientific analysis software.

Building a databrowser.

The process of building a databrowser involves several steps:

  1. cleaning up any problems with the source data so that they are consistent and well organized
  2. writing code that allows vetted statistical analyses to be run interactively
  3. writing code to create high quality scientific graphics based on the results of the analysis
  4. embedding the analysis and visualization code in a web-server based databrowser engine
  5. creating a user interface that allows users to quickly and easily send requests to the analysis and visualization engine running on the server

When properly designed, the code behind a good databrowser can encapsulate a huge amount of institutional memory about the scientific process. Ideally, databrowser graphics should be of high enough quality that they are immediately ready to be included in scientific publications.

Working with the Energy Export Databrowser

Selecting a Plot Type

The databrowser currently supports two distinct plot types:

Plots the hisorical evolution of production, consumption, imports and exports for a single resource within a nation or group of nations. Individual nations on the map are colored as importers or exporters. Plot options allow user specified scaling to allow for direct comparison between plots.
All Fuels
Plots the historical contribution of each resource in the database to total energy consumption. This allows users to see the evolution of the energy mix within a nation or group of nations. Plot options allow users to examine production or consumption.

Selecting a Resource

All energy resources from the British Petroleum 2017 Statistical Review are included in the databrowser -- coal, oil, natural gas, nuclear, hydro. Clicking on one of the "Resource" radio buttons will access data files for that resource while retaining all other user settings.

It is important to note that the Statistical Review does not contain consumption worksheets for nuclear and hydro power. It is assumed that all electricity produced from these resources is used internally. We are aware that this is a very poor assumption but it is beyond the scope of this dataset to keep track of electricity transfers between nations.

Selecting Units

The BP 2017 Statistical Review contains separate datasheets for each unit reported. A scientists we believe this to be unnecessary as a change in units should only represent a change in scaling. We have observed, however, that things are not so simple. As our goal is to be as faithful to the BP data management effort as possible, we have retained the values found in each datasheet. This means that the shape of the historical curves displayed by the databrowser will change subtly as one switches units.

If anyone has can explain to us why these differences exist in the database we would love to know!)

For data comparisons in the "All Fuels" plot type, it is important to be aware of the different assumptions in the two available units:

million tonnes of oil equivalent per year (mtoe)
Data in the nuclear and hydroelectric worksheets are scaled up by a factor of 1/0.38 (=2.63) so as to show "the equivalent amount of fossil fuel required to generate the same volume of electricity in a thermal power station".
Exajoules per year (J)
Data in the nuclear and hydroelectric worksheets are left unscaled so as to show the actual amount of 'potentially usable energy' from each source.

For a comparison of power produced from coal or gas fired power plants with power produced from nuclear or hydro power plants, it would be best to use units of 'mtoe'. For a more theoretical exploration of 'energy available' units of 'J' would be more appropriate.

Selecting Countries / Groups

The British Petroleum 2017 Statistical Review breaks out consumption and production data by country, continent and a few groupings like 'Former Soviet Union' and 'OPEC'. In the case of countries of the Former Soviet Union, all data prior to 1985 is lumped together as 'Former Soviet Union'. This means that individual countries like 'Ukraine' or 'Russian Federation' have no production/consumption data prior to 1985.

The code behind the Energy Export Databrowser makes it possible to calculate consumption/production statistics for any combination of countries. An initial application of this capability is found in the 'Interesting Groups' section of the 'Country / Group' selector. Choosing one of these mult-country groups will show the following:

  • Countries in the map are colored by whether they imported or exported in 2007.
  • The production/consumption graph represents the sum of all countries in the group.

The 'Interesting Groups' section includes the following abbreviations:

Former Soviet Union
Organization of Petroleum Exporting Countries
Organization for Economic Cooperation and Development
US, United Kingdom, France, Germany, Italy, Japan, Canada
Brazil, China, Indonesia, India, South Africa

Selecting Plot Options

Each plot type has its own set of optional plot settings that allow for modifications unique to that plot type.

Interpreting Results

Various interesting patterns appear in the data graphics. A few interpretations are provided here.

Peak Production

Uninterrupted by war or political upheaval and developed with the latest technology, the North Sea provides a very good example of a 'normal' (almost gaussian) production curve that is now past 'peak' production. It is anticipated that annual production volumes will continue to decline barring a dramatic new discovery.

North Sea Oil Production

Export Land Model

The 'Export Land Model' proposed by Jeffrey Brown and Samuel Foucher describes how developing nations, enriched by oil profits, will grow economically and increase their own consumption of energy resources. Declining production and increasing consumption can rapidly turn an exporting nation into one that requires imports as exemplified by ex-OPEC member Indonesia.

Indonesia Oil Production

Coal Fired Growth

Coal fired power plants are huge contributors to increased levels of CO2 in the atmosphere. They are also engines of growth for developing nations with access to coal. Coal fired the original Industrial Revolution in the British Isles and is now doing the same in many nations in Asia. The undisputed giant of coal users is China.

China Energy Consumption


One of the reasons nations go to war is to gain access to resources. However, in the case of energy resources, the damage to infrastructure inflicted by modern warfare can reduce rather than increase access to those resources. Nowhere is this more true than in Iraq.

  • Iran-Iraq War (1981-1988)
  • First Gulf War (1990-1991)
  • Sanctions (1991-2003)
  • Iraq War (2003-2011)
Iraq Oil Production

Domestic Consumption Only

In some countries in some years, production and consumption match. In these cases, the country will be colored gray in the map. This is often seen when looking at Natural Gas which is largely dependent upon pipelines for export. Until recently, Colombia had no means for exporting its Natural Gas and all production was consumed domestically.

Colombia Nat Gas Production