One of the key aspects relating to the transportation of anthropogenic carbon dioxide (CO2) for climate change mitigation as part of Carbon Capture and Storage (CCS) schemes is the composition of the CO2 stream to be transported. The specification of this stream has both technical and economic implications and, as CCS schemes start to become realised, the requirement to specify the CO2 stream quality is becoming more important.The aim of this work has been to analyse the effects of the composition of the CO2 stream from post-combustion, pre-combustion and oxyfuel capture processes on the hydraulic network design and the relative costs of the network. Several key conclusions have been drawn to inform the process of specifying the CO2 purity and to guide pipeline operators on the specification of a CO2 stream, for dense phase pipeline operation, on the basis of hydraulic design.The analysis has shown that impurity additions up to 2mol% did not affect the relative cost/km for the networks when compared to a pure CO2 equivalent in terms of the pipeline internal diameter and length. However, the inlet pressure to the network is increased for all of the compositions studied and in this respect, levels of hydrogen in particular should be limited to less than 1mol% to reduce inlet pressure and thereby compression costs.It has been demonstrated that direct connection pipelines from source to sink are the most expensive network options however, when designing a pipeline network, the size of the emitters, the phasing of entry into the network and the stability of the network in the event of interruptions in flow needs to be considered

The impurities present in carbon dioxide (CO2) streams for Carbon Capture and Storage (CCS) schemes are extremely important for CO2 pipeline and ship transportation affecting, for instance, the range of operation, safety considerations, fracture, cracking, corrosion control, dispersion in the event of a release, fluid density, operating pressure and temperature and the quantity of CO2 that can be transported. The range and levels of potential impurities present in captured CO2 from CO2 capture facilities will differ between sources and also between the capture technologies installed at the CO2 emission sources. However, the potential CO2 specifications that could enter the transport and storage systems, particularly from industrial sources, remain relatively under-researched. Consequently, the effect of these potential impurities in CO2 streams on CO2 transportation also needs to be understood. This paper summarises the main findings of an IEAGHG study, “Impact of CO2 Impurity on CO2 Compression, Liquefaction and Transportation”, commissioned to identify potential impurities and address the consequences of their impact on CO2 transportation

Climate change has been attributed to greenhouse gases with carbon dioxide (CO2) being the major contributor. Most of these CO2 emissions originate from the burning of fossil fuels (e.g. power plants). Governments and industry worldwide are now proposing to capture CO2 from their power plants and either store it in depleted reservoirs or saline aquifers (‘Carbon Capture and Storage’, CCS), or use it for ‘Enhanced Oil Recovery’ (EOR) in depleting oil and gas fields. The capture of this anthropogenic (man made sources of CO2) CO2 will mitigate global warming, and possibly reduce the impact of climate change. The United States has over 30 years experience with the transportation of carbon dioxide by pipeline, mainly from naturally occurring, relatively pure CO2 sources for onshore EOR. CCS projects differ significantly from this past experience as they will be focusing on anthropogenic sources from major polluters such as fossil fuel power plants, and the necessary CO2 transport infrastructure will involve both long distance onshore and offshore pipelines. Also, the fossil fuel power plants will produce CO2 with varying combinations of impurities depending on the capture technology used. CO2 pipelines have never been designed for these differing conditions; therefore, CCS will introduce a new generation of CO2 for transport. Application of current design procedures to the new generation pipelines is likely to yield an over-designed pipeline facility, with excessive investment and operating cost. In particular, the presence of impurities has a significant impact on the physical properties of the transported CO2 which affects: pipeline design; compressor/pump power; repressurisation distance; pipeline capacity. These impurities could also have implications in the fracture control of the pipeline. All these effects have direct implications for both the technical and economic feasibility of developing a carbon dioxide transport infrastructure onshore and offshore. This paper compares and contrasts the current experience of transporting CO2 onshore with the proposed transport onshore and offshore for CCS. It covers studies on the effect of physical and transport properties (hydraulics) on key technical aspects of pipeline transportation, and the implications for designing and operating a pipeline for CO2 containing impurities. The studies reported in the paper have significant implications for future CO2 transportation, and highlight a number of knowledge gaps that will have to be filled to allow for the efficient and economic design of pipelines for this ‘next’ generation of anthropogenic CO2.

Mechanical damage is recognized as a problem that reduces the performance of oil and gas pipelines and has been the subject of continuous research. The artificial neural network in the spotlight recently is expected to be another solution to solve the problems relating to the pipelines. The deep neural network, which is on the basis of artificial neural network algorithm and is a method amongst various machine learning methods, is applied in this study. The applicability of machine learning techniques such as deep neural network for the prediction of burst pressure has been investigated for dented API 5L X-grade pipelines. To this end, supervised learning is employed, and the deep neural network model has four layers with three hidden layers, and the neural network uses the fully connected layer. The burst pressure computed by deep neural network model has been compared with the results of finite element analysis based parametric study, and the burst pressure calculated by the experimental results. According to the comparison results, it showed good agreement. Therefore, it is concluded that deep neural networks can be another solution for predicting the burst pressure of API 5L X-grade dented pipelines.