Determination of lower and upper bounds of predicted production from history-matched models

We present a method to determine lower and upper bounds to the predicted production or any other economic objective from history-matched reservoir models. The method consists of two steps: 1) performing a traditional computer-assisted history match of a reservoir model with the objective to minimize the mismatch between predicted and observed production data through adjusting the grid block permeability values of the model. 2) performing two optimization exercises to minimize and maximize an economic objective over the remaining field life, for a fixed production strategy, by manipulating the same grid block permeabilities, however without significantly changing the mismatch obtained under step 1. This is accomplished through a hierarchical optimization procedure that limits the solution space of a secondary optimization problem to the (approximate) null space of the primary optimization problem. We applied this procedure to two different reservoir models. We performed a history match based on synthetic data, starting from a uniform prior and using a gradient-based minimization procedure. After history matching, minimization and maximization of the net present value (NPV), using a fixed control strategy, were executed as secondary optimization problems by changing the model parameters while staying close to the null space of the primary optimization problem. In other words, we optimized the secondary objective functions, while requiring that optimality of the primary objective (a good history match) was preserved. This method therefore provides a way to quantify the economic consequences of the well-known problem that history matching is a strongly ill-posed problem. We also investigated how this method can be used as a means to assess the cost-effectiveness of acquiring different data types to reduce the uncertainty in the expected NPV.     

The impact of surplus units from the first Kyoto period on achieving the reduction pledges of the Cancún Agreements

Countries with emission levels below their emission allowances have surplus Assigned Amount Units (AAUs) or other emission credits. Under the Kyoto Protocol, these surplus credits may effectively be carried from the first to a following commitment period. In the climate negotiations, various rules for carry-over and sale of surplus allowances have been put forward. This paper analyses the effect of these options on the reduction pledges for 2020, taking into account the estimated credits from the Clean Development Mechanism, Joint Implementation projects, and land-use activities for the first commitment period. For current Kyoto Protocol rules of unlimited carry-over of surplus allowances and limited carry-over of other credits, the environmental effectiveness of reduction pledges could be seriously undermined. For the group of countries that showed a willingness to participate in a second commitment period, it could imply that instead of an aggregated 2020 target resulting from the pledges of 18 to 28?% below 1990 levels by 2020, their emissions could return to business-us-usual emission projections. For the EU, a 30?% target by 2020 could imply higher emissions compared to a 20?% target, if surplus allowances would be used for achieving the 30?% but not for the 20?% target. Restricting the use of Kyoto surplus units to domestic use only, would limit the problem, but still seriously undermine the effectiveness of 2020 reduction targets.     

The role of the land use, land use change and forestry sector in achieving Annex I reduction pledges

Annex I Parties may receive credits or debits from Land Use, Land Use Change and Forestry (LULUCF) activities, contributing to achieving individual emission reduction targets. In the Durban climate negotiations, Parties agreed new LULUCF accounting rules for the second commitment period of the Kyoto Protocol (CP2). By using these new rules, this paper presents key differences among Parties at the minimum (assuming no additional action) and potential (assuming additional actions) contribution of the forest-related LULUCF activities in achieving the pledges for 2020. Overall, the potential contribution of LULUCF is relatively modest (up to about 2 % of 1990 emissions) for the EU, the Annex I Parties likely joining the CP2, and for the Annex I Parties that joined the CP1 as a whole. However, for specific Parties, LULUCF can make a substantial contribution to achieving the pledges. For New Zealand, for instance, the potential contribution of future LULUCF credits may equal 33 % of its 1990 emission level. For Australia, the pledges are expressed relative to 2000 emission levels including LULUCF emissions. Given that LULUCF emissions have strongly declined between 1990 and 2000, and a further decline in foreseen by 2020 (based on Australia’s projections), the minimum contribution of LULUCF to meet the Australian pledges appears to be about 19 % and 7 % relative to its 1990 and 2000 emission level, respectively. A further 3 % potential contribution is estimated from additional actions.     

Adaptation in integrated assessment modeling: where do we stand?

Adaptation is an important element on the climate change policy agenda. Integrated assessment models, which are key tools to assess climate change policies, have begun to address adaptation, either by including it implicitly in damage cost estimates, or by making it an explicit control variable. We analyze how modelers have chosen to describe adaptation within an integrated framework, and suggest many ways they could improve the treatment of adaptation by considering more of its bottom-up characteristics. Until this happens, we suggest, models may be too optimistic about the net benefits adaptation can provide, and therefore may underestimate the amount of mitigation they judge to be socially optimal. Under some conditions, better modeling of adaptation costs and benefits could have important implications for defining mitigation targets.     

Understanding river dune splitting through flume experiments and analysis of a dune evolution model

Forecasts of water level during river floods require accurate predictions of the evolution of river dune dimensions, because the hydraulic roughness of the main channel is largely determined by the bed morphology. River dune dimensions are controlled by processes like merging and splitting of dunes. Particularly the process of dune splitting is still poorly understood and – as a result – not yet included in operational dune evolution models. In the current paper, the process of dune splitting is investigated by carrying out laboratory experiments and by means of a sensitivity analysis using a numerical dune evolution model. In the numerical model, we introduced superimposed TRIAS ripples (i.e. triangular asymmetric stoss side‐ripples) on the stoss sides of underlying dunes as soon as these stoss sides exceed a certain critical length. Simulations with the model including dune splitting showed that predictions of equilibrium dune characteristics were significantly improved compared to the model without dune splitting. As dune splitting is implemented in a parameterized way, the computational cost remains low which means that dune evolution can be calculated on the timescale of a flood wave. Subsequently, we used this model to study the mechanism of dune splitting. Literature showed that the initiation of a strong flow separation zone behind a superimposed bedform is one of the main mechanisms behind dune splitting. The flume experiments indicated that besides its height also the lee side slope of the superimposed bedform is an important factor to determine the strength of the flow separation zone and therefore is an important aspect in dune splitting. The sensitivity analysis of the dune evolution model showed that a minimum stoss side length was required to develop a strong flow separation zone. Copyright © 2014 John Wiley & Sons, Ltd.     

How well do integrated assessment models simulate climate change?

Integrated assessment models (IAMs) are regularly used to evaluate different policies of future emissions reductions. Since the global costs associated with these policies are immense, it is vital that the uncertainties in IAMs are quantified and understood. We first demonstrate the significant spread in the climate system and carbon cycle components of several contemporary IAMs. We then examine these components in more detail to understand the causes of differences, comparing the results with more complex climate models and earth system models (ESMs), where available. Our results show that in most cases the outcomes of IAMs are within the range of the outcomes of complex models, but differences are large enough to matter for policy advice. There are areas where IAMs would benefit from improvements (e.g. climate sensitivity, inertia in climate response, carbon cycle feedbacks). In some cases, additional climate model experiments are needed to be able to tune some of these improvements. This will require better communication between the IAM and ESM development communities.     

Controllability,observability and identifiability in single-phase porous media flow

Over the past few years, more and more systems and control concepts have been applied in reservoir engineering, such as optimal control, Kalman filtering, and model reduction. The success of these applications is determined by the controllability, observability, and identifiability properties of the reservoir at hand. The first contribution of this paper is to analyze and interpret the controllability and observability of single-phase flow reservoir models and to investigate how these are affected by well locations, heterogeneity, and fluid properties. The second contribution of this paper is to show how to compute an upper bound on the number of identifiable parameters when history matching production data and to present a new method to regularize the history matching problem using a reservoir’s controllability and observability properties.     

RCP2.6: exploring the possibility to keep global mean temperature increase below 2��C

The RCP2.6 emission and concentration pathway is representative of the literature on mitigation scenarios aiming to limit the increase of global mean temperature to 2°C. These scenarios form the low end of the scenario literature in terms of emissions and radiative forcing. They often show negative emissions from energy use in the second half of the 21st century. The RCP2.6 scenario is shown to be technically feasible in the IMAGE integrated assessment modeling framework from a medium emission baseline scenario, assuming full participation of all countries. Cumulative emissions of greenhouse gases from 2010 to 2100 need to be reduced by 70% compared to a baseline scenario, requiring substantial changes in energy use and emissions of non-CO₂ gases. These measures (specifically the use of bio-energy and reforestation measures) also have clear consequences for global land use. Based on the RCP2.6 scenario, recommendations for further research on low emission scenarios have been formulated. These include the response of the climate system to a radiative forcing peak, the ability of society to achieve the required emission reduction rates given political and social inertia and the possibilities to further reduce emissions of non-CO₂ gases.     

Seabirds in the North Sea Demobilized and Killed by Polyisobutylene (C4H8)n (PIB)

This paper reports on a mass stranding of seabirds in the North Sea in December 1998. Hundreds of birds were washed ashore alive in Zeeland (SW Netherlands), covered in a whitish, sticky substance, and were transported to a rehabilitation centre. About 10 days later, more (dead) casualties washed ashore further to the north on Texel and along the mainland coast, again covered in a glue-like substance. Common guillemots Uria aalge, northern fulmars Fulmarus glacialis and common scoters Melanitta nigra were the most numerous birds affected in this incident. Both strandings were temporarily (10 days) and geographically separated (ca. 120 km apart), but were apparently caused by a single source of pollution. The meteorology at the time was consistent with the course of a single incident. At least 1100 seabirds were affected by this substance, soon identified as polyisobutylene (C₄H₈)_n. PIB is known as a non-toxic, non-aggressive substance. Volunteers cleaning the birds in the rehabilitation centre reported serious discomfort and dizziness and the soft parts of the PIB-affected birds found dead (bill, eye, throat, feet, webs) appeared to dissolve in a few days time. Both effects cannot be attributed to PIB, and are therefore unexplained. Although the dumping of PIB in the marine environment is not explicitly prohibited under MARPOL, the effects on wildlife observed are enough to plead for counter-measures.     

Variation in the climatic response to SRES emissions scenarios in integrated assessment models

Integrated assessment models (IAMs) have commonly been used to understand the relationship between the economy, the earth’s climate system and climate impacts. We compare the IPCC simulations of CO₂ concentration, radiative forcing, and global mean temperature changes associated with five SRES ‘marker’ emissions scenarios with the responses of three IAMs—DICE, FUND and PAGE—to these same emission scenarios. We also compare differences in simulated temperature increase resulting from moving from a high to a low emissions scenario. These IAMs offer a range of climate outcomes, some of which are inconsistent with those of IPCC, due to differing treatments of the carbon cycle and of the temperature response to radiative forcing. In particular, in FUND temperatures up until 2100 are relatively similar for the four emissions scenarios, and temperature reductions upon switching to lower emissions scenarios are small. PAGE incorporates strong carbon cycle feedbacks, leading to higher CO₂ concentrations in the twenty-second century than other models. Such IAMs are frequently applied to determine ‘optimal’ climate policy in a cost–benefit approach. Models such as FUND which show smaller temperature responses to reducing emissions than IPCC simulations on comparable timescales will underestimate the benefits of emission reductions and hence the calculated ‘optimal’ level of investment in mitigation.