The purpose of this thesis was to assess the driving forces behind CO2 emission intensities of oil and gas extraction on both Norwegian Continental Shelf (NCS) and UK Continental Shelf (UKCS). We were specifically interested in how the CO2-price have influenced emission intensity of oil and gas extraction as this is said to be one of the most important measurement to reduce CO2 emissions on the NCS. By using panel data with a sample of 147 offshore fields, of which 44 fields are from NCS and 103 from UKCS. We studied the periods 1997-2015 and 2006-2015 for NCS and UKCS, respectively.
We estimated the driving forces by mainly using a Random Effects model for panel data regression. We ran both an original model, which included all variables we found relevant, and a main model, which included only 11 of 19 variables from the original model. In addition to these two models, we also ran five additional estimations. The results in this analysis support several of earlier findings such as Gavenas (2014) and Gavenas et al. (2015).
6.1 Main findings
The first main finding is that the CO2-price was not significant in either of the two models. However, it could be the case that the CO2-price has had some indirect effect on emission intensity when it comes to e.g. investments and increased awareness around CO2 emissions on the offshore petroleum industry.
The dummy variable for fields located on UKCS generally enters with high statistical significance, suggesting that there is a difference between fields located on UKCS and NCS when it comes to emission intensity. In this analysis, we expected that the dummy for fields located on UKCS, would capture long-term effects of different CO2-price for NCS and UKCS that the CO2-price indicator variable was unable to capture. However, this turned out to have the opposite effect on emission intensity. As mentioned in Section 4.2, the emissions from UKCS are probably higher than the emission data indicates as there is as substantial difference between the obtained emission figures and the emission reported in both IOGP (2016) and Oil and Gas UK (2016). Further, when estimating with heterogeneous CO2-price effects, the CO2-price influenced emission intensity positively on NCS when excluding the dummy variable for fields located on UKCS. However, the CO2-price probably captures the differences between UKCS and NCS since the dummy is not included.
Our second main finding is that offshore fields tend to have higher emissions in its declining phase relative to their peak production level, and the effect is even stronger for fields on UKCS than on NCS.
Further, water injection enters with a significant effect on emission intensity, which strengthens the former conclusion.
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Our third main finding is that gas fields tends to have lower emissions than oil fields since emission intensity tends to increase with the share of oil in a field’s original reserve. We also find this when most electrified fields, which are mostly gas fields, are excluded from the model. This finding supports the findings of Gavenas et al. (2015). Also here is the effect even stronger for fields located on UKCS, where gas fields have 80 % lower emission intensity than oil fields on the UKCS. On the NCS, gas fields have 63 % lower emission intensity than oil fields.
In contradiction to Gavenas (2014) and Gavenas et al. (2015), suggest our estimation results that smaller fields have higher emission intensity. In addition, our estimations suggest that fields with significant water depth have higher emission intensity.
According to our estimations, gas flaring seemed to only be statistical significant for fields on the NCS, while not on the UKCS. The time trend only enters weakly positive significant in the original model.
Further, neither the share of oil in the field’s running production nor start-up year turned statistical significant. We also found a weak indication of a positive effect on emission intensity on the NCS when it comes to a lagged oil price. However, generally there was no statistical evidence of the oil and gas prices affecting emission intensity.
6.2 Limitation of the study
As mentioned before, there is significant difference between the emissions intensity based on data obtained from BEIS (2017) and the emission intensity reported in Oil and Gas UK (2016) and IOGP (2016). This may indicate that the emission data for UK is inadequate.
Further, we encountered some emission intensity values less than 1 kg CO2 per toe, where we tried two alternatives to deal with this problem. The first alternative was to drop emission intensity values less than one, and the second alternative was to replace the values less than one with one (cf. Section 4.2).
Thus, it could be argued either to use a different functional form than taking the natural logarithm, or to use a different method than the two alternatives mentioned above to avoid this estimation issue.
Another limitation of this study was in relation to connecting the satellite fields to their main fields.
Hence, there could be some characteristic error when connecting these fields. Thus, the estimation results would have been more accurate if each offshore field, both satellite and main field had reported emissions.
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6.3 Suggestion for further research
Only available emission figures for UKCS were in the period 2006-2015. To get a better understanding of the driving forces behind CO2 emission intensities on UKCS, study of data across a longer time may be of suggestion. Moreover, a longer period studied also applies for the NCS, where we have studied the years 1997-2015. If Norwegian CO2 emission figures before 1991 were available, we could compare before and after the introduction of the Norwegian CO2-tax to obtain a more precise picture of the CO2 -price.
Another possible approach is to include other GHGs such as methane since most natural gas consists of methane. Emission of methane may be relevant to study as methane is the second largest GHG after CO2. In 2015, emitted methane from offshore oil and gas extraction were 28 947 tonnes and 41 200 tonnes on NCS and UKCS, respectively (NOG 2016; Oil and Gas UK 2016; SSB 2016). Methane stood for 5 % and 7 % of the total GHG emissions from offshore oil and gas extraction, while CO2 stood for 95 % and 90 % of the GHG emissions, respectively (Oil and Gas UK 2016; SSB 2016).
It is also possible to include other explanatory variables such as the amount invested in each field or whether the reservoir type or well type (horizontal vs. vertical wells) influence emission intensity.
Alternatively, to look into the use of energy-efficient technology at field level, as this thesis did not consider technological characteristics as explanatory variables. Further, it is also possible to distinguish between different sources of CO2 emission from the petroleum industry to a greater extent, such as combustion of gas or diesel in turbines.
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