Increase In Net Present Value Research Articles

ARTIFICIAL INTELLIGENCE FOR OPTIMIZED WELL CONTROL AND MANAGEMENT IN SUBSURFACE MODELS WITH UNPREDICTABLE GEOLOGY

A comprehensive control policy structure utilizing Artificial Intelligence (AI) is presented for closed-loop management in subsurface models. Conventional Closed-Loop Optimisation (CLO) approaches entail the iterative implementation of information assimilation, past synchronization details, and effective optimizing procedures. Information assimilation is more difficult when there is uncertainty in the geological approach and the specific model conclusions. Closed-Loop Reservoir Monitoring (CLRM) offers a control strategy that promptly correlates flow information obtained from wells, as typically accessible, to appropriate well stress configurations. The rule is characterized by time-based compression and gate-based converter sections. Learning is conducted during a preprocessing phase utilizing geological modeling derived from various geological settings. Illustrative instances of oil extraction using water insertion, utilizing both 2 and 3-dimensional geological designs, are shown. The AI-oriented technique demonstrates a 17.2% increase in Net Present Value (NPV) for 2D instances, an additional 31.5% for 3D cases compared to the effective optimization of previous models, and a 1-6.5% enhancement in NPV relative to standard CLRM. Based on the methods and variable configurations examined in this study, the controlling policy method yields a 71.34% reduction in processing expenses compared to conventional CLRM.

Optimization of offshore wind farm cluster transmission system topology based on Stackelberg game

Offshore wind energy is pivotal in the global energy transition, with a global installed capacity reaching 64.3 GW by 2022 and an expected annual increase of 60.2 GW over the next decade. This study aims to optimize the topology of transmission systems (TS) for offshore wind farm (OWF) clusters using Stackelberg game theory. The OWF investor (OWFI) acts as the leader, optimizing investment returns while considering wake effects, and the offshore TS operator (OTSO) follows by adjusting transmission strategies to reduce costs. The analysis includes the wake effects within OWF clusters and their impact on power generation efficiency. Simulation results demonstrate that the proposed model can balance stakeholder interests and enhance the economic viability of OWF clusters, showing a potential increase in net present value (NPV) by up to 30 %. This study validates the practical application of the Stackelberg game model in optimizing OWF cluster TS topology, contributing to more efficient and cost-effective renewable energy integration.

Conversion of the planted forest with pinus to grain production in the Brazilian conditions: a study showing the economic perspectives

The Brazilian roundwood production of planted forest (PF) is large and turns Brazil, a prominent player on a global scale. A study was established on a farm located in Tibagi, Paraná, Brazil. We simulated two scenarios: A (continuity planting of pinus), and B (conversion of pinus to corn/soybean production). Results showed that both the productions of pinus and the rotation of soybean/corn are viable economic alternatives. If make-decided, the conversion of pinus to corn/soybean production also presented optimal with an increase of net present value, annual net present value, and internal rate of return, respectively from 9.8 %; R$ 1,519.48; and R$ 160.57 (PF), to 13.7 %; R$ 3,389.50; R$ 304.93 (soybean/corn). The rotation of soybean/corn presented a positive economic flux after the 4th crop-year due to the high initial cost of stump-removal. While, the pinus showed a positive economic flux after the 7th crop-year with the thinning/harvest in the 7th, 10th, 14th, 16th, and 20th years. Based on our results and from literature, we conclude that there is an increase of grain areas due to the influence of global grain consumption and high commodity prices, which can cause a conversion of PF to grain production areas due to higher better economic gains. However, farmers should maintain the economic-health of the property with the diversity of viable economic crops (i.e., pinus and corn/soybean), and the positive impact of planted forest on environmental sustainability.

Opportunities for utilizing waste cooking oil in crude to petrochemical process: Novel process design, optimal strategy, techno-economic analysis and life cycle society-environment assessment

The efficient utilization of waste cooking oil (WCO) in petrochemical and high-quality gasoline production could reduce food safety issues and boost the new energy industry's sustainable development. The co-processing of WCO, vacuum gas oil, and light cycle oil (LCO) by the fluid catalytic cracking unit could achieve process integration, which exhibits promising economic prospects for manufacturing large amounts of low-cost petrochemicals. Herein, we proposed a novel process, i.e., hierarchical LCO hydrotreating combined with two-stage riser catalytic cracking processes (HTMP-plus). Based on industrial test data, the process model of HTMP-plus was first developed on the Aspen HYSYS Petroleum Refining platform and optimized operating parameters were conducted. In this novel process, lighter LCO fractions were directly recycled to the second riser reactor, and heavier LCO fractions were fed into the selective hydrotreating unit. This strategy intensified the conversion of WCO and LCO, reduced hydrogen consumption, and improved the economic benefit. Furthermore, the life cycle society-environment evaluation was performed. Compared with the conventional HTMP process, the HTMP-plus process could produce 5% more propylene and high-quality gasoline for every ton of mixed feedstock and provide up to a 31% increase in net present value. Moreover, the HTMP-plus process consumes approximately 5% less non-renewable energy and discharges 2% less CO2 equivalent and 16% less wastewater based on one-million-USD dollars total output value.

Produce petrochemicals directly from crude oil catalytic cracking, a techno-economic analysis and life cycle society-environment assessment

Achieving direct catalytic cracking of crude oil to produce low-cost petrochemicals is a milestone technology for the transformation of refinery from “fuel type” to “chemical engineering type”. Herein, we first established the crude oil catalytic cracking process and identified the key process parameters affecting ethylene and propylene yields. Meanwhile, the crude oil direct steam cracking process was selected as a comparative process for the process economic, social and environmental performance by an improved life cycle society-environment assessment method. The improvement direction, suitable preheating temperature and higher cracking temperature, are given from the aspect of process though systematic integration and intensification. Results show the conversion rate of the catalytic cracking process is 86.10%, while the steam cracking process is only 76.71%. Furthermore, the utilization efficiency of carbon and hydrogen in the catalytic cracking process is 1.29 and 1.47 times higher than the steam cracking process, respectively. As for the society-economic performance, the catalytic cracking process provides up to 65% and 11% increase in net present value and total output value. As for the environmental performance, the catalytic cracking process consumes approximately 4% less non-renewable energy and has 31% less waste water generation. The results in this study harbour tremendous guiding significance to the design of crude oil directly efficient conversion to petrochemicals.

Multi-objective Optimization of CO2 Recycling Operations for CCUS in a Brazilian Pre-Salt Benchmark Model

This study evaluates the potential of recycling carbon dioxide (CO2) in the associated gas for Carbon Capture Utilization and Storage (CCUS) in pre-salt carbonate reservoirs. We performed compositional subsurface modelling of a hypothetical field for multi-objective optimization, aiming at minimizing carbon emissions whilst maximizing the project’s economics. Although no absolute reduction in total CO2 emissions was met with economic improvement, all simulated CCUS scenarios yielded a lower carbon footprint oil, with 41% reduction in operational emissions and up to 20% increase in Net Present Value. The best CCUS case presented break-even oil price of 39.2 USD/STB and CO2 abatement cost of negative 92.4 USD/tCO2 abated, also showing significant reduction in number of squeeze treatments and cost of calcite scale management.

Developing a new technique for the simultaneous optimization of both segmented time and injection rate for water flooding reservoirs: An analysis of Shengli Oilfield XIN-42 reservoir block

The adjustment and control of the water injection rate is a commonly used method for increasing the cumulative oil production of waterflooded reservoirs. This article studies the production optimization problem under the condition of a fixed total water injection rate. The production process is divided into several segments. Considering the correlation between the segment’s time intervals and the well’s injection rate distribution, a simultaneous optimization of both segmented time and injection rate is proposed for enhancing net present value. Both empirical simulations and field application demonstrate that the suggested methods produce the highest increase in net present value – of approximately 13% and 10%, respectively – and significantly improve water flooding efficiency compared to other conventional schemes, such as segmented oil production optimization, cumulative oil production optimization and Bang-Bang control. The proposed methods under a 2-segment division increase oil production efficiency and greatly reduce adjustment costs.

Innovations in engineering: analysis of the increase effect in net present value

The article discusses the construction of mathematical models for assessing economic conditions under which a positive effect of using loan capital in the implementation of innovative and investment projects in engineering is possible, leading to an increase in net present value (NPV). Based on the constructed models, the authors obtained economic and mathematical relations (linking the parameters of innovation and investment projects: investor profitability standard, loan capital rate, time it was entered into the financial and temporal scheme of the project, the time it began to pay off financial obligations and its duration), which determine the increase effect of NPV due to the corresponding structure of investment capital. In the form of functions of the project parameters, analytical expressions are obtained to determine the critical value of the loan rate, the time of its input, as well as the rate of return on the investor and at which the effect of an increase in the net present value of the project becomes possible. The mathematical relations and the economic conclusions drawn on their basis are backed by practical results, given in a graphic form.

Integrated Multiscale Design, Market Participation, and Replacement Strategies for Battery Energy Storage Systems

Increased dependence on non-dispatchable energy sources has created a need for flexible energy storage systems capable of providing peak shaving and ancillary services. This work develops a computational framework to optimize sizing, replacement, and market participation strategies for battery energy storage systems. A multiscale linear programming formulation is proposed that spans real-time market decisions (minutes) to sizing and replacement decisions (years) while explicitly considering capacity loss due to degradation. These optimization problems include millions of variables and constraints, but can be efficiently solved using modern algorithms. Several case studies explore tradeoffs between market participation, degradation, power-to-energy ratio, and replacement strategies using historical energy and ancillary service price data from CAISO. Findings emphasize that simultaneously transacting both energy and ancillary services in day-ahead and real-time markets can provide a four to five fold increase in net present value compared to only buying/selling energy in the day-ahead market. Optimization also reveals market participation strategies that effectively manage degradation leading to an optimal energy-to-power ratio of less than 1 MWh/MW for NaS batteries. Results also show that developing ideal degradation-free batteries would improve net present value by 20%. This emphasizes that judicious management of degradation, sizing, and markets is critical.

Empirical development of parsimonious model for international diffusion of residential solar

We develop a new parsimonious model of residential solar diffusion that, with only two regression parameters and one independent variable, reasonably explains empirical observations. Additional solar customers resulting from an increase in Net Present Value (NPV) are modeled as a normal distribution. This leads to adoption as a function of NPV being the integral of the Gaussian, producing the error function, which demonstrates S-curve behavior commonly seen in technology diffusion. Empirical analysis for five regions (three U.S. states: Arizona, California, and Massachusetts; and two countries: Germany and Japan) from 2005 to 2016 shows a consistent relationship between annual adoption per million households and NPV. Non-linear regression indicates good agreement between data and the error function model, the adoption rate peaking at an NPV of $7100/kW with standard deviation of $4110/kW. Consumer purchases of rooftop solar across multiple regions are explained with a single variable, making this model simpler than traditional diffusion approaches. A novel implication of the model is that the subsidy cost to stimulate additional solar adoption increases as the technology becomes cheaper. This is because the same subsidy is paid to all consumers, including those who would have purchased solar without subsidy.

An Optimisation Approach for Long-Term Industrial Investment Planning

The industrial sector has a large presence in world energy consumption and CO2 emissions, which has made it one of the focal points for energy and resource efficiency studies. However, large investments are required to retrofit existing industrial plants, which remains the largest barrier to implementing energy saving solutions. Process integration methods can be used to identify the best investments to improve the efficiency of plants, yet their timing remains to be answered using an optimisation approach. Even more critically, such decisions must also account for future investments to avoid stranded or regretted investments. This paper presents a method incorporating investment planning over long time horizons in the framework of process integration. The time horizon is included by formulating the problem using multiple investment periods. Investment planning is conducted using a superstructure approach, which permits both commissioning and decommissioning of units in the beginning of each period. The method is applied to a large case study, with an industrial cluster neighbouring an urban centre to also explore options of heat integration between industries and cities. Compared to the business-as-usual operation, optimal investment planning improves the operating cost of the system by 27% without budget constraints and 16–26% with constraints on budget and investment periods, which is reflected as an increase in net present value and a decrease in CO2 emissions. In all cases, the operating cost benefits pay off the investment in less than two years. The present work is efficient in finding energy saving solutions based on the interest of industries. This method adds additional perspectives in the decision-making process and is adaptable to various time horizons, budgets and economic constraints.

Managerial flexibility role on financial investment analysis: a case study of public housing

The limitations of Discounted Cash Flow (DCF) method for capturing the opportunity value phenomenon in the uncertainty of housing investment analysis cause difficulties in the decision-making process for the investors. Flexibility factor becomes the obstacle for investors in project uncertainty. Real Options Analysis (ROA) is an important factor included in the DCF method because it offers managerial flexibility in the uncertainty of housing investment decision making. Flexibility in ROA is a right and investors do not have an obligation to respond to uncertainty in project investment. In this research, the type of flexibility on ROA used is an option to carry out promotional activities. The research results indicate that promotional activities affect the increase in Net Present Value (NPV) so that the benefits are maximized. Comparison of the results of investment analysis between ROA and DCF methods indicates an added value due to the existence of such flexibility. The investment simulation of ROA method was conducted using Monte Carlo method approach. The role of flexibility from the simulation is obtained by increasing the added value by 5.2%, and optimal promotion occurs in the first two years of investment.

Grade uncertainty embedded in long term scheduling: stochastic mine planning

Abstract The inclusion of grade uncertainty for multivariate mineral deposits is of great importance for the correct management of subsequent decisions involved in mining planning. Mapping grade uncertainties allows maximization of profit and resource extraction. In this article, the co-simulation turning band algorithm is applied with the aim of predicting multivariate grade uncertainties. Moreover, a probabilistic analysis in long term mining sequencing is proposed in order to select the best given grade scheduling uncertainty derived from the simulations. A case study in a phosphate mine shows that the correlation of co-simulated variables honors the original data and there is an improvement in the project by an increase in Net Present Value (NPV) planning considering grade uncertainties. A comparison is performed with the results derived from the selected schedule and the results using the model based on kriged grades.

Assessing the Financial Value of Patient Engagement: A Quantitative Approach from CTTI\u2019s Patient Groups and Clinical Trials Project

BackgroundWhile patient groups, regulators, and sponsors are increasingly considering engaging with patients in the design and conduct of clinical development programs, sponsors are often reluctant to go beyond pilot programs because of uncertainty in the return on investment. We developed an approach to estimate the financial value of patient engagement.MethodsExpected net present value (ENPV) is a common technique that integrates the key business drivers of cost, time, revenue, and risk into a summary metric for project strategy and portfolio decisions. We assessed the impact of patient engagement on ENPV for a typical oncology development program entering phase 2 or phase 3.ResultsFor a pre-phase 2 project, the cumulative impact of a patient engagement activity that avoids one protocol amendment and improves enrollment, adherence, and retention is an increase in net present value (NPV) of $62MM ($65MM for pre-phase 3) and an increase in ENPV of $35MM ($75MM for pre-phase 3). Compared with an investment of $100,000 in patient engagement, the NPV and ENPV increases can exceed 500-fold the investment. This ENPV increase is the equivalent of accelerating a pre-phase 2 product launch by 2½ years (1½ years for pre-phase 3).ConclusionsRisk-adjusted financial models can assess the impact of patient engagement. A combination of empirical data and subjective parameter estimates shows that engagement activities with the potential to avoid protocol amendments and/or improve enrollment, adherence, and retention may add considerable financial value. This approach can help sponsors assess patient engagement investment decisions.

A stochastic optimization formulation for the transition from open pit to underground mining

As open pit mining of a mineral deposit deepens, the cost of extraction may increase up to a threshold where transitioning to mining through underground methods is more profitable. This paper provides an approach to determine an optimal depth at which a mine should transition from open pit to underground mining, based on managing technical risk. The value of a set of candidate transition depths is calculated by optimizing the production schedules for each depth’s unique open pit and underground operations which provide yearly discounted cash flow projections. By considering the sum of the open pit and underground mining portion’s value, the most profitable candidate transition depth is identified. The optimization model presented is based on a stochastic integer program that integrates geological uncertainty and manages technical risk. The proposed approach is tested on a gold deposit. Results show the benefits of managing geological uncertainty in long-term strategic decision-making frameworks. Additionally, the stochastic result produces a 9% net present value increase over a similar deterministic formulation. The risk-managing stochastic framework also produces operational schedules that reduce a mining project`s susceptibility to geological risk. This work aims to approve on previous attempts to solve this problem by jointly considering geological uncertainty and describing the optimal transition depth effectively in 3-dimensions.

CO2 Capture from Sulphur Recovery Unit Tail Gas by Shell Cansolv Technology

A significant driver for the climate change effect is CO2 emission from the sources where fossil fuel is consumed to generate energy. Capturing and sequestration of CO2 from these emission sources is a practical way to mitigate GHG emission impact. However the cost of CCS projects has been a major obstacle to implementing these technologies worldwide. Two main aspects which influence the cost of a CO2 capture project are the CO2 utilization pathway and the CO2 capture technology selection.CO2-Enhanced Oil Recovery (EOR) can be a very good potential pathway to increase the revenue of the CCS project. CO2-EOR also can be an attractive way of using CO2 in areas such as Middle East where the oil and gas reservoirs are mature. However one of the main constraints can be limited access to CO2 especially where no power plant is close to a potential oil reservoir.For technology selection, the choice is typically between Pre- and Post-Combustion. Pre-combustion CO2 capture technologies have been deployed in oil refineries & gas processing plants for decades, but the main source for CO2 emissions in these facilities is often off-gas (also known as acid gas) which is usually sent to the flare system or incinerator. These off-gases are at low pressure, so a compression system is required to pressurize the gas before sending it to the Pre-combustion CO2 capture unit. On the other hand, Post-combustion CO2 capture technology can often require an additional desulfurization step to remove SO2 which can potentially result to higher operational and capital cost as well as waste management and complexity of operation. This paper will discuss the deployment of Shell Cansolv technology to capture CO2 from off-gas downstream of the Sulfur Recovery Unit (SRU) in a single train, potentially as a new CCS application in the oil and gas sectors.The off-gas from Tail Gas Treatment Unit (TGTU) downstream of the SRU will usually contain a higher amount of CO2 compared to coal and gas power plants. The absorption affinity of Shell Cansolv solvent at low pressure off-gas compared to other pre-combustion technologies allows the elimination of the primary compression system located upstream of the CO2 capture unit. Since there is H2S slippage from the TGTU absorber overhead, the amine should be characterized in terms of absorption affinity and stability in the reduced environment. The impact of H2S on amine performance in terms of degradation has been investigated in comparison to a post-combustion application where H2S is incinerated and converted to SOx. SOx contaminates amine to form Heat Stable Salt (HSS), so it needs to be removed prior to the post-combustion CO2 capture unit in a separate FGD unit (Flue Gas Desulfurization). Shell Cansolv DC amine in pre-combustion lineup absorbs both H2S and CO2 in a single absorber so incinerator and FGD unit is not required compared to post-combustion applications. Shell Cansolv DC amine has been tested to remove up to 99% CO2 which is higher than the 90% typical capture rate for most post-combustion applications. The other advantage of this application is the ability to operate at high temperature (∼60 C). This is often a key design parameter especially in the Middle East where most applications are considered hot climate applications. All design parameters of the CO2 capture unit such as liquid per gas ratio (L/G), stripping factor at the regenerator side and absorber packing height have been evaluated and optimized to reduce both capital and operational costs of the project. Eventually, in a case study, an economic comparison was conducted and the result indicated potentially more than 40% reduction in the cost of a CO2 capture unit as well as same magnitude increase in Net Present Value (NPV) compared to pre-combustion technology.

The equipment utilisation versus mining rate trade-off in open pit mining

ABSTRACTThis paper investigates the potential value adding role that ‘schemes of exploitation’ may have as part of the open pit mine planning process. The deployment of loading equipment within the push-back of an open-pit mine ultimately determines the ‘mining rate’. Traditional mine planning processes seek to adopt schemes of exploitation that maximise the utilisation of the loading equipment as this will typically minimise mining cost. This paper argues that this does not always lead to the creation of value. A case-study demonstrates that alternative schemes of exploitation, with higher mining costs and lower shovel productivity can actually generate greater value. The results show an increase in Net Present Value from US$920M to US$966M when a less productive configuration of four shovels is set instead of a configuration of two shovels. A sensitivity analysis is presented to show the economic and technical conditions that can favour this new proposal.

Systematic Approach to Identifying Economically Feasible and Environmentally Benign Methods of Recycling Ash on a Regional Scale

This study systematically assessed and compared four ash recycling possibilities, namely forest fertilization, landfill construction, road construction, and road stabilization through the use of cost-benefit analysis and life cycle assessment methods. The results indicated that forest fertilization with ash was the most economically attractive method with a 60% increase in the net present value compared to ash landfilling, while reducing the environmental impact by 0.3%. On the contrary, road construction with ash resulted in a 13% reduction in the environmental impact and an increase in net present value of 25%. Landfill construction with ash was overall the least attractive proposition.

Designing Efficient College and Tax Policies

The total social benefits of college education exceed the private benefits because the government receives a share of the monetary returns in the form of income taxes. We study the policy implications of this fiscal externality in an optimal dynamic tax framework. Using a variational approach we derive a formula for the revenue effect of an increase in college education subsidies and for the excess burden of income taxation caused by the college margin. We also show how the optimal nonlinear income tax problem is altered by the college margin. Our modeling assumptions are strongly guided by the recent structural labor literature on college education. The model incorporates multidimensional heterogeneity, idiosyncratic risk and borrowing constraints. The model matches key empirical results on college enrollment patterns, returns to education and enrollment elasticities. Quantitatively, we find that a marginal increase in college subsidies in the US is at least 70 percent self-financing through the net-present value increase in future tax revenue. When targeting this increase to children in the lowest parental income tercile, it is even up to 165 percent self-financing. The excess burden of income taxation is only slightly altered by the college margin and therefore the optimal Mirrleesian income tax schedule is barely affected as well, in particular if subsidies are set at their optimal level.

Designing Efficient College and Tax Policies

The total social benefits of college education exceed the private benefits because the government receives a share of the monetary returns in the form of income taxes. We study the policy implications of this fiscal externality in an optimal dynamic tax framework. Using a variational approach we derive a formula for the revenue effect of an increase in college education subsidies and for the excess burden of income taxation caused by the college margin. We also show how the optimal nonlinear income tax problem is altered by the college margin. Our modeling assumptions are strongly guided by the recent structural labor literature on college education. The model incorporates multidimensional heterogeneity, idiosyncratic risk and borrowing constraints. The model matches key empirical results on college enrollment patterns, returns to education and enrollment elasticities. Quantitatively, we find that a marginal increase in college subsidies in the US is at least 70 percent self-financing through the net-present value increase in future tax revenue. When targeting this increase to children in the lowest parental income tercile, it is even up to 165 percent self-financing. The excess burden of income taxation is only slightly altered by the college margin and therefore the optimal Mirrleesian income tax schedule is barely affected as well, in particular if subsidies are set at their optimal level.