Disruption in the pipeline: Legal challenges in a digitised oil and gas sector
The oil and gas sector faces a new wave of challenges and opportunities as a result of technological innovation and disruption. Over the coming decades, ever-hastening advances in technology – from machine learning to robotic automation – will have a profound impact on the way that oil and gas reserves are located, extracted, distributed and consumed.
To survive and thrive, oil and gas companies will need to adopt radically new strategies to integrate these new technologies across the value chain whilst continuing to navigate complex regulatory environments, geopolitical risk, disputes and market disruption.
This article considers key legal issues which both incumbent participants and new market entrants will need to navigate effectively in order to succeed in a digitised oil and gas market, be they investors, operators or off-takers.
Data as the new oil?
Effective use of data underpins economic success at all stages of the oil and gas supply chain (see Table 1). Advances in computing speed and capacity will enable companies to collect, analyse and interpret these data in increasingly innovative and powerful ways.
All of these types of data hold significant value. Some data types – such as subsurface data and models – are inherently valuable in and of themselves, given the investment required to generate them. Increasingly, though, the value of data depends on its susceptibility to enhanced processing technologies. For example, large sets of raw data are particularly well-suited to machine learning techniques, which are capable of efficiently identifying patterns and anomalies such as geological faults.
Further data opportunities are presented by combining data sets from third party sources, such as correlating pipeline performance data with weather statistics, or retail and distribution logistics
data with consumer travel patterns. The effective combination of data can expose previously unseen patterns and behaviours. However, the exploitation of such data combinations requires the wider adoption of suitable platforms, common technologies and commercial regimes for sharing and commercialising data.
Dynamically linking data analysis with live operation feeds can generate significant value. For example, data from operating plant and machinery can be used by next-generation software suites which are capable of merging historical and current data sets into dynamic "digital twin" frameworks, such as those used by aircraft engineers. These fully detailed structural simulation models, when combined with live sensor data and machine learning analytics techniques, can provide project operators with unprecedented insight into their assets and the ability to evaluate design and operation improvements safely and efficiently.
The increasing value and vulnerability of non-tangible information and intellectual assets will be central to the future oil and gas legal landscape, and merit careful legal protection to preserve competitive advantage. However, under English law, there is no legal right to "own" data. Instead, companies seeking to protect valuable information must rely on a combination of confidentiality and intellectual property laws together with contractual rights and restrictions. Superimposed on this foundation is a fast-evolving web of data-focussed regulations, notably in relation to data protection and cyber security, and it remains to be seen how such regulations will develop in the future as governments react to the challenges of information governance.
In order to navigate these conflicting legal issues, it is essential that oil and gas companies map their data flows carefully to identify in detail what data they collect, how and where they process it and the purposes and objectives of such processing. Businesses can then make an informed assessment as to what internal technical and organisational measures to adopt in order to comply with sector-specific regulations – such as restrictions on the export of geological information – as well as to respond effectively to data security incidents. In addition, it will be increasingly essential for stakeholders to invest in cyber-defences which can keep pace with the ever-evolving risks of cyber-attacks.
Rise of the machines
If data is the life blood of oil and gas industry operations, then heavy engineering is its muscle and logistics are its skeleton. The sector is responsible for some of the largest and most sophisticated construction projects on the planet. Oil and gas is an inherently physical industry (see Table 2), and by automating physical tasks, sector stakeholders can improve efficiency, improve safety, circumvent human error and reduce overheads.
Physical assets are also likely to enjoy a longer usable lifespan as predictive and automated maintenance increases the efficiency of both proactive and reactive repairs and upgrades. Disruption of traditional oil and gas operations by autonomous robotics is likely to be considerable.
The key legal issue which arises from any physical process is liability. Who is liable for accidents which may cause extensive damage to property, injury to humans and
HERBERT SMITH FREEHILLS
DISRUPTION IN THE PIPELINE
Table 1 - Key data across the oil and gas supply chain
EXAMPLES OF IMPORTANT DATA
Exploration and appraisal
geological and seismic imaging data from surveys and pilot wells are harvested to assess reservoirs
static data generated by reservoir models and software are used to design field architecture
Drilling and production
live data from rig, downhole and facility sensors are monitored to optimise performance
geospatial data are exploited to optimise routes and location planning
consumption and purchasing patterns and trends are recorded at points of sale and used for marketing and pricing purposes