At the same time, klemmers noted that the basic dimensions of the growth of global demand for lng remain, “for the time being, regasification facilities and gas pipelines are being built throughout asia to prepare for increased demand when supply arrives.” this may alleviate market concerns about oversupply of lng。
At the same time, klemmers indicated that as domestic demand for natural gas increased and production declined, indonesia, malaysia and algeria could become net import markets in the future, and they were expected to add nearly 50 million tons of new lng demand by 2040。
The shell report on the future of liquefied natural gas (lng) was released in february this year, predicting that global demand (lng demand will grow by about 60 per cent to 630-718 million tons) by 2040, a figure higher than last year's projection of 625-685 million tons。
According to the company, this was mainly due to economic growth in asia, reduced emissions from heavy industry and transport, and the influence of artificial intelligence. More natural gas will be needed globally for power generation, heating and refrigeration, industry and transport to achieve development and decarbonization goals。
For example, in the chinese market, demand in the industrial sector will be a key driver. According to kramers, “china is pursuing a strategy of diversification, including domestic production growth, pipeline imports and lng procurement. Shells will deepen cooperation with chinese lng importers and promote china's future decarbonization process.”
The global energy transition has proceeded as well as radical transformation strategies by the oil and gas giants, but with little success. As oil prices have fallen in recent years and the profits of international oil and gas companies have fallen further, they are returning to traditional hydrocarbon operations to reverse the decline。
On 25 march this year, as the world's largest lng trader, shells were released to investors in new york with an updated strategy for 2025 and beyond。
Shell expects that its total production from upstream and integrated natural gas operations will increase by 1 per cent per annum by 2030, while achieving a complex annual growth rate of 4 to 5 per cent per annum in the volume of lng sales and maintaining a substantive liquid production of 1. 4 million barrels per day by 2030。
Shells also plan to increase the distribution of shareholders from 30-40 per cent to 40-50 per cent of past operating cash flows. By 2028, its annual expenditure will fall to $20-$22 billion。
In the context of the low-carbon transition, the company proposed “to create more value with fewer emissions” and committed itself to halving emissions within the range i and ii of operational controls by 2030 and achieving a net zero emission target by 2050。
Kramers informed the interface that shells would incorporate low-carbon technologies in project design. For example, carbon capture and storage (cs) technologies were integrated into projects in qatar to reduce emissions at the production end; canadian plants used hydropower as external electricity to build large energy plants with the lowest carbon emission intensity globally; and the emirates project introduced renewable energy to reduce the carbon footprint。
Currently, artificial intelligence is active in a wide variety of industries, including energy。
From kramer's point of view, when it comes to ai in the field of energy, there are two aspects: first, the energy needed by ai, and second, the use of ai to optimize energy production。
On the one hand, ai brings about an increase in energy demand. Facilities such as the ai data centre push up energy demand, and global energy projections rise as a result of such expected demand, becoming an important industry issue。
Ai, on the other hand, optimizes energy production efficiency. For example, the process is optimized, with the shell plant in nigeria setting precision equipment parameters to increase production and reduce carbon emissions through ai; and predictive maintenance, where companies use ai to analyse data to predict the risk of internal corrosion in the pipeline, advance preventive maintenance and improve operational reliability。
