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Multiphase flowmeters are important to monitor oil wells, as they allow operators to obtain a real-time estimate of the production. However, due to its high installation cost, uncertainty, and reading errors, the oil and gas industry started to invest in virtual meters, mathematical models that can obtain the oil and gas flow forecast using the instrumentation already available in the well, such as pressure and temperature sensors. The purpose of this article is to develop a virtual multiphase flow predictor using artificial intelligence models such as Long Short-Term Memory (LSTM), Gate Recurrent Units (GRU), Multi-Layer Perceptron (MLP) neural networks and deep learning. As input data, this paper uses a public database available on the Oil and Gas Authority (UK) to train the models and demonstrate the possibility of predicting multiphase flow with a reasonable error margin, proving that the method is efficient in estimating well production rates. • In the oil industry, it is important to measure the production from each well. • A Virtual Meter is a low-cost alternative. It can measure multiphase flow without any additional equipment. • This paper proposes a Virtual Meter using neural networks such as MLP, LSTM, GRU and deep learning combinations. • Prediction performance was evaluated using the Oil and Gas Authority (OGA) public database and it shows promising results. • Experiments using a combination of multiple layers shows this type of prediction takes advantage of deep learning techniques. [ABSTRACT FROM AUTHOR]

Hydrocarbon well decommissioning requires the long-term sealing of abandoned wells. Current plug and abandonment (P&A) operations are not always able to address all potential fluid migration pathways, resulting in the possible upwards migration of hydrocarbons from formations penetrated by the wellbore. The development of innovative materials to improve well sealing remains a major challenge. This paper presents a proof of concept for the use of colloidal silica (CS)-based grout to improve the sealing performance of P&A operations. CS is a non-toxic suspension of silica nanoparticles (<100 nm) undergoing gelation upon destabilisation. Due to its excellent penetrability and controllable gel time, CS has the potential for repairing fine-aperture cracks within the cement sheath, at the cement/casing interface, or within a cement plug, where the penetration of cementitious grouts is restricted due to their relatively large particle size. In this study, the suitability of CS grout for deployment up to 1500 m depth was successfully demonstrated. Firstly, a range of CS grout mixes were investigated to test the feasibility of grout emplacement considering a timescale of 2 h for pumping operations from the surface to depth. Secondly, to investigate the sealing performance, the CS grout was injected into fractured cement cores (0.2 and 0.5 mm fracture aperture) and exposed to pressure and temperature conditions simulating downhole scenarios up to 1500 m depth (based on gradients for North Sea, UK). Fracture permeability upon water injection was assessed pre- and post-treatment. This work found that permeability values after treatment were reduced by three orders of magnitude, thus confirming the potential of CS grout for repairing fine-aperture cracks. • Use of colloidal silica (CS) based grout to provide long-term sealing of abandoned oil&gas wells to improve plug and abandonment operations. • CS grout can penetrate fine-aperture cracks within the cement sheath, at the cement/casing interface, or within a cement plug. • Treatment with CS grout at conditions up to 1.5 km depth reduces the permeability of fractured cement cores by several orders of magnitude. [ABSTRACT FROM AUTHOR]

Many recent discoveries in the UKCS have been economically marginal and comparatively small such that they are unable to be developed on a standalone basis. Nevertheless, there is a proliferation of production facilities and transport infrastructure that can, on accepting a tariff, process hydrocarbons from these smaller-sized oil and gas fields, thereby contributing to the UK Government's strategy of maximising economic recovery (MER). However, the empirical dimensions of cost-sharing arrangements between a field owner (host field or hub) and tie-in (satellite) fields are not well examined in the literature although they influence long-term economics in matured oil provinces. In this paper, we develop a mixed integer programming optimisation model to analyse how these third-party access to infrastructure issues impact MER in the UKCS. A first-best situation with only one regional operator is empirically compared with the actual situation of multiple ownership. We then assess the impact of different infrastructure unbundling provisions via pipeline tariff choices and their interaction with the fiscal regime on the net present value (NPV) and other project metrics such as timings of hub and field shutdowns. We find that differences in field ownership, tariff choice and changes to the fiscal regime impact the overall NPV of field developments. Our results also show that having a progressive fiscal regime in a mature basin such as the UKCS is important to support continued operations under low oil prices while increasing the government's take at high prices. The cost-sharing effect shows that imposing strict cost-sharing rules does not change overall project valuations, even in a low oil price scenario. An additional contribution to the extant literature is that tariff determination could be based on cost-sharing rules that enjoin each field tieback to a hub to pay a split tariff, comprised of a fixed cost of service (access charge) and variable (marginal) costs. • Presents MIP model for analysing economic dependencies of infrastructure assets. • Ownership style, choice of tariffs, and fiscal regime impact overall field value. • Reducing marginal tax rates improves profitability, reflecting neutrality and progressivity. • Tariffs are decisive as to whether satellite or user fields are developed. • Tariff determination to maximise MER should be based on two-part cost-sharing. [ABSTRACT FROM AUTHOR]

The final stage in the life of a hydrocarbon well is decommissioning, which aims to ensure that the original integrity of the cap rock is restored and all penetrated sub-surface formations with flow potential are isolated with an "eternal perspective" (OIL&GAS_UK, 2018). Well plug and abandonment (P&A) costs constitute a significant proportion of the total decommissioning expenditure. Careful planning and execution is always required, because a failed P&A often calls for costly and complex remedial operations, and can potentially result in significant environmental costs, reputational damage and financial loss. The high cost of well P&A operations and the increasing number of North Sea wells approaching the end of their economic life have resulted in a growing need to identify and develop new approaches to well P&A that are both fit-for-purpose and cost-effective. The development of a tool to support a risk-based analysis of P&A designs has been identified as one of the means for achieving these twin objectives. This paper describes the first stage in this process - the development of a novel modelling framework that can provide a quantitative assessment of the leakage risk associated with each well P&A design scenario over a specified period of time. The framework is built on a commercial, grid-based, numerical, reservoir simulator and can be used to model most North Sea wells scheduled for P&A during the coming years. Preliminary results are presented to illustrate the value that can be derived from the framework. The importance of understanding the ranking of model inputs on the basis of their impact on modelled leakage rates, and hence the significance of any associated uncertainties, is also illustrated using an example which shows cement absolute permeability (k) rather than relative permeability (k r) to be a more critical determiner of hydrocarbon leakage rates for the P&A cases examined. The modelling results also demonstrate the robustness of a grid-based numerical simulation approach to well P&A system modelling. • Full-scale P&A well models were built using finite-difference numerical simulators. • Steady-state responses of the numerical models were validated against Darcy's law. • X-shaped k r were adequate for modelling gas-water flow through defective cement. • Impact of k r on flowrate was negligible for high permeability (i.e. defective) cement. • Average permeability values were adequate for representing defective cement barriers. [ABSTRACT FROM AUTHOR]