It is often said that Oil Majors should transition to renewables and become Energy Majors. But what is the best balance based on modern portfolio theory? Our 7-page paper answers this question by constructing a mean-variance optimisation model. We find a c0-20% weighting to renewables can maximise risk-adjusted returns. 5-13% is ideal. But beyond a c35% allocation, both returns and risk-adjusted returns decline rapidly to utility-type levels.
This data-file calculates the CO2 intensity of oilfield supply chains, across ten different resources, as materials are transported to drilling rigs, frac crews, production platforms and well pads.
Different resources can be ranked on this measure of supply chain CO2-intensity: such as the Permian, the Gulf of Mexico, offshore Norway, Guyana, pre-salt Brazil and Middle East onshore production (chart above).
Underlying the calculations are modeling assumptions, for both onshore and offshore operations, each based on c15 input variables. You can change the inputs to run your own scenarios, or test the most effective ways to lower supply-chain CO2.
This data-file tabulates Permian CO2 intensity based on regulatory disclosures from 20 of the leading producers to the EPA in 2018. Hence we can calculate the basin’s upstream emissions, in tons and in kg/boe.
The data are fully disaggregated by company, across the 20 largest Permian E&Ps, Majors and independents; and across 18 different categories, such as combustion, flaring, venting, pneumatics, storage tanks and methane leaks.
A positive is that CO2 intensity is -52% correlated with operator production volumes, which suggests CO2 intensity can be reduced over time, as the industry grows and consolidates into the hands of larger companies.
This data-model calculates risk-adjusted returns available for different portfolio weightings in the energy sector, as companies diversify across upstream, downstream, chemicals, corporate, renewables and CCS investments. The methodology is a mean-variance optimisation based on modern portfolio theory.
Should Oil Majors become Renewable Energy Majors? Our model indicates returns would decrease by allocating more capital to renewables, but certain renewable allocations can nevertheless increase risk-adjusted returns, as quantified using Sharpe Ratios.
Please download the model to test the impacts of flexing portfolio weightings; either at our own risks, returns and diversification benefits; or under your own assumptions which can be tweaked in the model.
Gas and diesel engines can be particularly inefficient when idling, or running at 20-30% loads. At these levels, their fuel economy can be impaired by 30-80%. This is the rationale for hybridizing engines with backup batteries: the engines are always run at efficient, 80-100% loads, including to charge up the batteries, which can better cover lower intensity energy needs.
Hybrid passenger cars are the best known example, since Toyota re-introduced them in the late 1990s. c25-30% energy savings are achieved, including through engine down-sizing and regenerative breaking
Industrial applications are also increasingly taking hold as battery costs come down, achieving even higher, 30-65% energy savings. This data-file summarizes a dozen examples, from oil and gas, marine, construction and even the machinery at LNG plants.
This data-file estimates the CO2 intensity of drilling oil wells, in our usual units of kg/boe. The calculations are conducted bottom-up, based on fuel consumption at onshore, offshore and deep-water rigs; plus drilling days and typical resource volumes per well.
Drilling wells is not the largest portion of the oil industry’s total CO2 intensity. Nevertheless there is a 50x spread between the best and worst barrels, which is wider than other categories we have screened.
Prolific fields will have the lowest drilling-CO2 intensities, particularly where they are onshore (e.g., Saudi Arabia). Infill wells at mature deepwater fields may have the highest drilling-CO2.
Refining has the highest carbon footprint in global energy. To improve, we find better catalysts are needed. Uniquely, they could cut CO2 by 15-30%, while also uplifting margins. Catalyst science is under-going a digitally driven transformation. This 25-page note identifies the leaders.
CO2 intensity of oil refineries could rise by 20% due to IMO 2020 regulations, according to the estimates in this data-file, if a refinery chooses to convert all its high-sulphur fuel oil into low-sulphur diesel.
The drivers are an extra stage of cracking, plus higher-temperature hydrocracking and hydrotreating, which will also have the knock-on consequence of increasing hydrogen demands.
Higher CO2 intensity conflicts with the industry’s aim of lowering its net emissions, and a 20% increase would effectively undo 30-years of prior efficiency gains in the refining industry.
Catalysts matter for refinery energy and CO2 intensity, as is shown in this data-file: It tabulates temperature and pressure conditions, disclosed for different refinery units, based on over 50 patents from leading energy Majors.
The average refinery process takes place at 450C. But variability is high. Hence our data-file explains the variations as a function of the different catalyst compositions, being pioneered by the different companies.
Combining all the best-in-class new catalysts in the datafile, we think the average refinery could save 5kg/bbl of CO2 intensity: across hydrocracking, FCCs, steam cracking, coking, dewaxing, hydrotreating, alkylation and reforming.
This data-file tabulates the energy intensity and resultant CO2 intensity of the US refining industry, source by source, year by year, back to 1986.
Emissions of refining a barrel of crude in the US have fallen at a 0.5% CAGR over the past c30-years, from 36kg/boe in 1986 to 31kg/boe in 2018.
US refineries are increasingly fueled by natural gas and merchant steam, while own use of oil, coal and oil products have been phased out.