The influence of bubble clouds on acoustic propagation in the surfzone

High-frequency propagation close to an active surf line is explored with 12and 100-kHz propagation paths together with measurements of bubble clouds, bubble size distributions, and waves. Breaking waves inject massive bubble plumes that are mixed downwards from the roller region by intense turbulence. If these injections follow one another at intervals less than the time taken for the bubbles to rise to the surface, acoustic signals will be continuously blocked, forming an acoustical barrier that effectively inhibits any propagation. Occasionally, waves break seaward of this barrier. In this case, dense bubble clouds are mixed down beneath the air entrainment zone, but there is sufficient time for them to disappear before succeeding breakers, allowing intermittent high-frequency propagation recharge the bubble field. The duration and shape of signal dropouts are then determined by the selective removal of bubbles by buoyancy and dissolution. In addition to turbulence created by the air entrainment process, a lower level of continuous background turbulence may be generated by interaction of residual currents with the wave boundary layer. Our observations illustrate the variable character of acoustic blocking by bubble clouds and serve as a basis for quantitative analysis of these effects with a 2D propagation model coupled to 2D models of bubble cloud evolution and background turbulence     

Zero carbon energy system pathways for Ireland consistent with the Paris Agreement

The Paris Agreement is the last hope to keep global temperature rise below 2°C. The consensus agrees to holding the increase in global average temperature to well below 2°C above pre-industrial levels, and to aim for 1.5°C. Each Party’s successive nationally determined contribution (NDC) will represent a progression beyond the party’s then current NDC, and reflect its highest possible ambition. Using Ireland as a test case, we show that increased mitigation ambition is required to meet the Paris Agreement goals in contrast to current EU policy goals of an 80–95% reduction by 2050. For the 1.5°C consistent carbon budgets, the technically feasible scenarios' abatement costs rise to greater than €8,100/tCO₂ by 2050. The greatest economic impact is in the short term. Annual GDP growth rates in the period to 2020 reduce from 4% to 2.2% in the 1.5°C scenario. While aiming for net zero emissions beyond 2050, investment decisions in the next 5–10 years are critical to prevent carbon lock-in.

Key policy insights

• Economic growth can be maintained in Ireland while rapidly decarbonizing the energy system.

• The social cost of carbon needs to be included as standard in valuation of infrastructure investment planning, both by government finance departments and private investors.

• Technological feasibility is not the limiting factor in achieving rapid deep decarbonization.

• Immediate increased decarbonization ambition over the next 3–5 years is critical to achieve the Paris Agreement goals, acknowledging the current 80–95% reduction target is not consistent with temperature goals of ‘well below’ 2°C and pursuing 1.5°C.

• Applying carbon budgets to the energy system results in non-linear CO₂ emissions reductions over time, which contrast with current EU policy targets, and the implied optimal climate policy and mitigation investment strategy.

     

Parameter identification of minifrac numerical tests using a gradient boosting-based proxy model and genetic algorithm

In recent years, the petroleum industry has devoted considerable attention to studying fluid flow inside fracture channels due to the discovery of naturally fractured reservoirs. The behavior prediction of these reservoirs is a well-known challenging task, in which the initial stage consists of identifying reservoir hydromechanical parameters. This work proposes an artificial intelligence-based approach to identify hydromechanical parameters from borehole injection pressure curves acquired through minifrac tests. This approach combines proxy modeling with a stochastic optimization algorithm to match observed and predicted borehole pressure curves. Therefore, a gradient boosting-based proxy model is built to predict borehole pressure curves, considering a proper strategy to develop time series modeling. Moreover, a Bayesian optimization algorithm is applied to compute the gradient boosting hyperparameters. In this optimization scenario, this paper proposes an appropriate objective function established from the assumed time series prediction strategy and the k-fold cross-validation. Finally, a genetic algorithm is adopted to identify unknown hydromechanical parameters, solving an inverse problem. Based on the proposed workflow, a study of the importance of the hydromechanical parameters is developed. To assess the methodology applicability, the approach is employed to identify parameters in synthetic and field minifrac tests. The results present how this approach can adequately identify hydromechanical parameters of hydraulic fracturing problems.