An unconventional resource is an umbrella term used in petroleum industry energy resources tapped in reservoirs other than conventional ones. The porosity and permeability of unconventional reservoirs are less porous and permeable and require advanced techniques of exploration. Generally, the extraction of these resources is challenging on both technical and economic grounds. Still, gradual technological upliftment and intense global energy demands are paving the way to explore these resources.
Three primary reasons played a key role in the popularity of unconventional resources in recent years. The major one being the abundant presence of unconventional resources and low degree of conventional resources recovery. Global unconventional oil resources are equivalent to conventional oil resources, whereas global unconventional gas resources are far more than conventional gas resources.
EIA recently released its latest International Energy Outlook (IEO), which expects energy demand to grow by nearly half worldwide, between 2012 and 2040. The demand in developing countries will jump by almost 71 per cent while the rise will be ~18 per cent for developed nations.
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The advancement in technology, including cost-effective methods of exploration and industrial automation, is another factor contributing to the popularity of unconventional resources. The introduction of advanced technology has converted economically & technically challenged reserves into commercially viable reserves. Horizontal drilling and hydrofracturing are some of the important breakthroughs; the petroleum industry has got.
Around 84 per cent of recoverable unconventional resources are situated in regions like Russia, Asia Pacific, North America, and Latin America. Most of the unconventional oil and gas resources are accumulated in passive continental margins and account for around 49 per cent of the world's undiscovered resources. On the other hand, foreland basins and continental rift basins, both individually account for approximately 20 per cent of the world's total unconventional resources. Finally, the craton basins contain the world's 11 per cent of the world's undiscovered unconventional resources.
The global resource of tight oil, heavy oil, natural bitumen, and oil shale oil is about 412×109 t combined, and the global resource extent of tight gas, coalbed methane and shale gas are 921.9×1012 m3. North America, South America and Asia are the global leaders having maximum recoverable resources of unconventional oil. On the other hand, Asia Pacific, Russia, and North America are the global leaders of recoverable unconventional gas.
One of the most important breakthroughs in the extraction of Unconventional resource is the introduction of Hydraulic Fracturing technique. It produces fractures in oil and gas-bearing formations with less porosity and permeability, stimulating the flow within the reservoir and increase the recoverable volume. Fractures are created by pumping an enormous quantity of pressurized fluids that mainly contain water and proppants along with some acidizing agents. After the completion of the injection process, the hydrocarbon present in the reservoir is activated by the internal pressure of rock formations, and it starts flowing towards the surface through the wellbore.
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The other crucial technique is horizontal drilling which is used to drill a well horizontally. It increases the contact between reservoir and borehole, creating a better production interface in low porous and low permeable reservoirs, which is impossible to achieve in traditional vertical wells.
Both horizontal drilling and hydraulic fracturing and, have opened new avenues for oil and gas development, with an emphasis on natural gas reservoirs, for example, coalbed, shale, and tight sands.
What is an Absolute Advantage? Absolute advantage is one of the key macroeconomic terms, which is based on the principles of Capitalism and is often utilised in international trade-related decisions. Absolute advantage refers to the competence of a company, region or country to produce goods or services in an efficient manner compared to any other economic entity. The efficiency in production can be achieved by: Production of the same quantity of good or services as produced by other entity by utilising fewer amount of resources Production of a higher quantity of good or services as produced by other entity by using the same amount of resources What is the Significance of Absolute Advantage? Different countries or businesses possess a different set of ability owing to their location, soil composition, weather, infrastructure, or human resource skills. When applied in the right direction, various factors may pan out to offer more cost-effectiveness and hence build absolute advantage of the entity in comparison to others. The absolute advantage remains one of the critical determinants for the choice of the goods or services to be produced. Absolute advantage in a particular area often translates into profitability in the area. The profit margin increases by the achievement of cost efficiency, allowing the entity to ensure higher profitability over the competitors. For example, let us assume that the US can produce ten high-quality aircrafts utilising a specific amount of resources. China, on the other hand, can build 6 similar quality aircrafts using the same amount of resources. Thus, in the production of an aircraft, the US holds Absolute Advantage Let’s say the US has the ability to manufacture a certain amount of steel using 10 tonnes of iron ore. China, on the other hand, can produce the same quantity of steel using 8 tonnes of iron ore.Here, China here holds Absolute Advantage in the production of steel. How Countries Build Absolute Advantage? While natural conditions, which include climatic factors, geometry, topography, cannot be altered for achieving absolute advantage, the countries use the underlying factors strategically in their favour. Furthermore, factors of production are focused at by many companies or nations for building absolute advantages. Some of the strategies for building absolute advantage includes: Development of Technological Competencies- The implementation of innovative or latest technological innovations allows the entities to lower their production cost, facilitating absolute advantage. Enhancing Skills of Human Resources- The improvement in the cost-efficiency, along with the quality of the products, is targeted through imparting varying skill development programs. Many countries subsidize or aid the apprentice or labour training for enhancing the absolute advantage in trade. Improving Infrastructure- The infrastructure enhancement in the form of road, telecommunications, ports, etc. can be useful in enhancing the cost-effectiveness across different industries. What Do We Understand by Comparative Advantage Vs Absolute Advantage? Evaluating the comparative advantage introduces the concept of opportunity cost, which is the deciding factor to determine the production of particular goods or services. Opportunity cost refers to the potential benefits associated with the next best possible alternative which is missed out when one option is chosen over another. The Absolute advantage simply considers the capability of a business or region to deliver goods or services in the most efficient manner. The Comparative Advantage, however, also takes into account the benefits that are forgone if an entity decides for production of a particular product or services. Comparative advantage, based on the notion of mutual benefits, is often used in international trade deals. The Comparative advantage has been the major factor driving the outsourcing of services in search of cheap labour. Understanding through an Example For instance, country A can produce ten televisions with the same amount of resources with which it can make 7 laptops. The opportunity cost per television is 7/10 or 0.7 laptops. Meanwhile, the opportunity cost per laptop is 10/7 or 1.42 television. It highlights that country A is forsaking the production of 0.7 laptops if it is deciding to manufacture one television. On the other hand, it is missing out the opportunity to manufacture 1.42 televisions for every single laptop manufactured. Now, say Country B’s opportunity cost for producing a television is 0.5 laptop, and that of producing laptop is 2 televisions. Then, country B will have a comparative advantage in making televisions, and country A will have comparative advantage in producing laptops. It has to be noted that despite country A having absolute advantages in both the products, it would be mutually beneficial for both the countries if country B produces television while country A produces laptops. Do You Know About Absolute Advantage Theory by Adam Smith? The concept of Absolute Advantage was indicated by Adam Smith in his book called ‘Wealth of Nations’ which focusses on International trade theory. Adam Smith, in his book attacked on the previous mercantilism theory, which mainly stressed for economies to maintain trade surplus in order to command power. The Absolute Advantage theory considered that the countries possess different ability with respect to the production of varying goods or services. It argued that it is not necessary that a state may hold an absolute advantage in the production of all goods, and here the relevance of trade comes into play. It advocates that countries should produce those goods over which they hold a competitive advantage. It would allow the countries to make the same amount of goods using few resources or in less time. The theory propagates the relevance of trade for economic sustainability. What Are the Limitations of the Absolute Advantage Theory? The assumptions used in the Absolute Advantage Theory by Adam Smith may limit the application in real bilateral trade. The limitations of the theory by Adam Smith include: Smith assumed that the productive capabilities of a country could not be transferred between the two countries. However, in practical terms, the competitive scenario aids the nations to acquire new capabilities and acquire new resources, especially in the technological and human resource skill aspects. The two-country trade which was used as a basis for the theory does not consider the trade barriers levied. The present scenario, however, is strikingly dominated by trade wars between economies. Nations impose huge tariffs, import duties and other type of barriers to promote local manufacturers. Absolute Advantage theory assumes that the trade between the two nations will take place only if each of the two economies holds an absolute advantage in one of the commodities traded. However, in general, countries despite not holding absolute advantage are engrossed in international trade, boosting their economic setup.
What is Data Analytics? Data Analytics involves a set of quantitative and qualitative approaches and processes that can be used to determine useful information for business decision-making. The process involves various patterns and techniques, including: extracting a raw database, and categorising it to identify and analyse the behaviour, relation and connection of the results. The ultimate goal is to acquire valuable information in order to make decisions for businesses’ benefit and productivity. In today's competitive times, most companies chalk out their business plan with the help of data analytics. With organisations becoming customer-service oriented, data analytics has become a critical tool to reach the target audience in an effective manner while understanding their requirements. Once data is collected, it is analysed and stored according to organisations’ requirements. The data analysis process has multiple layers involved, and its diverse modules are not just used in businesses but also in science and social science fields. Rather than making decisions based on just available information, one can utilise data analytics in examining the data in standard ways and churning out the results from it. It has been observed that companies generally make decisions based on past references and future outcomes. Data analytics appears advantageous in providing useful information towards this end. Why do Businesses Need to Use Data Analytics? Many data analytics’ tools and softwares are readily available these days. These systems use resources, such as machine learning algorithms and automation. Data scientists and analysts are counted amongst the leading career options as well. These professionals use data analytics techniques while researching and presenting useful information for businesses to increase productivity and gain. The process helps companies understand their target audience and determine effective ways to cater to their needs. Data analytics can further be used to design strategies in marketing campaigns and promotions and also evaluate its results. Data analytics is primarily used in business-to-consumer (B2C) processes to boost business performance and improve the bottom line. There are data collection firms which gather consumer information and provide it to the businesses so that the companies can effectively influence the market. The collected data is not only used to understand and impact consumer behaviour but also determine market economics and its practical implementation. The data used in the process can be either be data collected in the past or newly updated data. There are various methods to manage consumer and market information. It may come directly from the customers or potential customers or can be purchased from the data collection vendors. The data primarily includes audience demographics, behavioural patterns and expense threshold. How Can Data Analytics be Effectively Used in Business Processes? Data analytics is an ever-evolving technique. Earlier, the data was collected manually, but with the rise of internet and technology, data is now collected online with the help of search engines and social media platforms. Subsequently, the information is analysed through available software. Here is a list of some key steps businesses can follow to leverage the benefits of data analytics: Set up crucial metrics: This step reduces the guesswork and provide data-based insights to the businesses. Before embarking on the data analytics process, it is vital to determine the goal for your business. Analysing customer data helps in understanding conversion rate, consumer spending ability, demographics etc. The results of the analysis can support the businesses while making decisions in launching an advertising or marketing campaign. Similarly, the unwanted data can be erased from the database so that the brands can focus on their right target audience. The relevant metrics will change the course of the company and push it in the right direction. Moreover, once your key metrics are set, even when the market conditions change in the future, you can adjust the metrics according to the requirement and achieve the results. Set a clear module: It is important to examine the data correctly by avoiding common mistakes. An ambiguous path can produce confusing insights while wasting time and energy of businesses. Therefore, it is recommended to draw a clear goal in order to achieve actionable insights. The data, when collected from different sources, need to be merged accurately in the analytics model. Businesses can modulate their data analytics systems either manually or through automation. There are various data modelling practices available in the market. The best use of these techniques can simplify the process of modelling complex data. Data visualisation: Once the relevant data is collected, and the modules are set to analysis, visualisation of that data will assist in understanding the information correctly. When the businesses have an acute knowledge of what their target audience wants, they can then focus on strategising advertisement and content, which matches the consumers' interest. It is the critical step in the data analytics process to distinguish insights from information. Not everyone is comfortable dealing with numbers. Hence, ensuring that key stakeholders understand essential points and information can be displayed in a visually appealing format seem crucial to capitalise on data effectively. Right tools to implement insights:Having access to data and insights can get overwhelming. However, the information is worthless if the businesses are unable to implement it successfully. While it is important to collect the data and set critical metrics and modules to analyse it, it is also imperative to translate the data into practical actions. The eventual goal is to improve sales or grow profits. It is ultimately in the marketers' hands to transform the gained insights into a successful implementation. The consumers' insights should be incorporated while establishing a marketing plan and at all decision-making steps.
What is Data Mining? Data mining is a process that facilitates the extraction of relevant information from a vast dataset. The process helps to discover a new, accurate and useful pattern in the data to derive helpful pattern in data and relevant information from the dataset for organization or individual who requires it. Key Features of data mining include: Based on the trend and behaviour analysis, data mining helps to predict pattern automatically. Predicts the possible outcome. Helps to create decision-oriented information. Focuses on large datasets and databases for analysis. Clustering based on findings and a visually documented group of facts that were earlier hidden. How does data mining work? The first step of the data mining process includes the collection of data and loading it into the data warehouse. In the next step, the data is stored and managed on cloud or in-house servers. Business analyst, data miners, IT professionals or the management team then extracts these data from the sources and accordingly access and determine the way they want to organize the data. The application software performs data sorting based on user’s result. In the last step, the user presents the data in the presentable format, which could be in the form of a graph or table. Image Source: © Kalkine Group 2020 What is the process of data mining? Multiple processes are involved in the implementation of data mining before mining happens. These processes include: Business Research: Before we begin the process of data mining, we must have a complete understanding of the business problem, business objectives, the resources available plus the existing scenario to meet these requirements. Having a fair knowledge of these topics would help to create a detailed data mining plan that meets the goals set up by the business. Data Quality Checks: Once we have all the data collected, we must check the data so that there are no blockages in the data integration process. The quality assurance helps to detect any core irregularities in the data like missing data interpolation. Data Cleaning: A vital process, data cleaning costumes a considerable amount of time in the selection, formatting, and anonymization of data. Data Transformation: Once data cleaning completes, the next process involves data transformation. It comprises of five stages comprising, data smoothing, data summary, data generalization, data normalization and data attribute construction. Data Modelling: In this process, several mathematical models are implemented in the dataset. What are the techniques of data mining? Association: Association (or the relation technique) is the most used data mining technique. In this technique, the transaction and the relationship between the items are used to discover a pattern. Association is used for market basket analysis which is done to identify all those products which customer buy together. An example of this is a department store, where we find those goods close to each other, which the customers generally buy together, like bread, butter, jam, eggs. Clustering: Clustering technique involves the creation of a meaningful object with common characteristics. An example of this is the placement of books in the library in a way that a similar category of books is there on the same shelf. Classification: As the name suggests, the classification technique helps the user to classify and variable in the dataset into pre-defined groups and classes. It uses linear programming, statistics, decision tree and artificial neural networks. Through the classification technique, we can develop software that can be modelled so that data can be classified into different classes. Prediction: Prediction techniques help to identify the dependent and the independent variables. Based on the past sales data, a business can use this technique to identify how the business would do in the future. It can help the user to determine whether the business would make a profit or not. Sequential Pattern: In this technique, the transaction data is used and though this data, the user identifies similar trends, pattern, and events over a period. An example is the historical sales data which a department store pulls out to identify the items in the store which customer purchases together at different times of the year. Applications of data mining Data mining techniques find their applications across a broad range of industries. Some of the applications are listed below: Healthcare Education Customer Relationship Management Manufacturing Market Basket Analysis Finance and Banking Insurance Fraud Detection Monitoring Pattern Classification Data Mining Tools Data mining aims to find out the hidden, valid and all possible patterns in a large dataset. In this process, there are several tools available in the market that helps in data mining. Below is a list of ten of the most widely used data mining tools: SAS Data mining Teradata R-Programing Board Dundas Inetsoft H3O Qlik RapidMiner Oracle BI
What are ETFs? ETFs are similar to funds where pooled money of investors is managed by a fund manager, who runs the ETF. These funds invest in equity, debt, commodity or any other asset class, depending on its offering. Good read: Mastering the Basics of Investing in ETFs Price of the ETF is based on a value of net assets in the fund and is subject to change each trading day consistent with underlying changes in the value of net assets. Since ETFs are traded in markets just like shares, the quoted price of an ETF either reflects a discount to its NAV or a premium to its NAV. Investors have flocked to ETFs because of low-cost proposition and opportunity to take exposure in a specific pool of assets, which are professionally managed by an investment team with the investment manager. Some ETFs are also used as a proxy to define sentiment in an underlying sector, commodity or index since ETFs are actively traded in market hours, incorporating the latest information in prices. Fund management businesses have continued launching new and innovative ETFs, which have seen great demand over the past. Read: Gold ETFs register massive capital influx; while PDI, GPP, ERM, AME, RED Under Investors’ Lens Large and popular ETFs have also defied liquidity problems because of large scale investor participation. But it remains a problem with lesser-known ETFs with small market participation. ETFs also pay distributions to the holders that are either derived through interest income, dividend income or capital gain. Active and Passive ETFs With ETFs markets growing strongly as ever, there remains a divide between active fund managers and passive fund managers. Passive investment strategies have grown immensely popular among market participants over time. This strategy is cost effective. Many seasoned investors such as Warren Buffett, John C Bogle- founder of the Vanguard Group have endorsed passive ETFs. Active ETFs do not track a benchmark, and performance is not tracked to any given index. These funds are based on countries, sectors, market capitalisation, asset classes, etc., and active investment management allows a manager to beat the returns delivered by broader markets or indices. If you look at the great investors like Warren Buffet, Philip Fisher or Peter Lynch, they have set themselves as a preamble for active investors, and their record of delivering sustainable returns over the long term continues to attract investors to active alleys of markets. Since Passive ETFs are designed to match returns of respective benchmarks, there is no scope of delivering outperformance no guarantee that fund will not underperform the benchmark. However, the expenses charged to investors are relatively lower compared to Active ETFs. Passive ETFs are cheaper than Active ETFs because the use of resources is limited in the former. Since they are designed to match the benchmark and its underlying securities, trading in Passive ETFs is mostly automated running on algorithms, and stock picking is not required, thereby no research. Read: ETFs: Investors Up the Ante and ETFs Run the Show for Long-Term Returns ETFs based on asset classes and style Sector ETFs: These are the most common type of ETFs in market. Sector ETFs track specific sectors like Information Technology, Consumer Staples, Consumer Discretionary, Metal & Mining. These are similar to index funds but are actively traded in stock exchanges. Equity ETFs: Equity ETFs may include equity-focused Sector ETFs. As the name suggests equity, these funds invest in stocks independently or are benchmarked to a specific index. Perhaps, Equity ETFs are the most common ETFs. Fixed Income ETFs: These funds invest in fixed income instruments and pay distributions out of the interest earned on bonds. Further Fixed Income ETFs can be separated as investment-grade ETFs, high-yield ETFs, Government bond ETFs. Commodity ETFs: Commodity ETFs invest in physical commodities like precious metal, agricultural goods, natural resource. These funds include products like Gold ETFs, Oil ETFs, Grain ETFs, Silver ETFs. Good read: Investing in Commodity ETFs Short ETFs: Also known as inverse ETFs, these funds are designed to benefit when the benchmark is falling. Short ETFs hold short positions in the benchmark index futures or constituents of the index to benefit from fall in value or prices. To know more about short selling read: Minting Money While the Asset Price Tanks; Enter the World of Short Selling Leveraged ETFs: Leveraged ETFs use derivatives to amplify the returns and risks of a fund. These are also called geared ETFs. Leveraged ETFs may also hold equity or bonds along with the derivatives to amplify the net asset value movement of funds. Do read: All You Need to Know About Exchange Traded Funds Why investors prefer ETFs? Passive investment vehicles continue to appear compelling to a large investor base, and there are numerous reasons driving the demand for passive investment vehicles. Low-cost and no minimum investment: ETFs have lower expenses compared to traditional mutual funds, and most of the funds have no minimum investment criteria. As a result, the market for ETFs has grown strong, due to its reach to investors with limited capital. Must read: Mutual Funds vs. ETFs: Which Are Better? Exposure to specific asset classes: Investors with large portfolio also use ETFs to enter to into specific asset classes like Gold ETF or Commodity ETF, but not limited to sector ETFs, theme-based active ETFs like technology, mobility, e-commerce etc. Portfolio diversification: ETFs provide investors with an opportunity to diversify a portfolio of concentrated stocks by including exposure to specific sectors, indices, and commodities. More importantly, the diversification is available at a low-cost investment, which further drives the need for ETFs in a portfolio. Accessibility: It is perhaps the most compelling value ETFs provide to investors. Since ETFs are available on stock exchanges like shares, investor participation remains strong, and some popular ETFs boast high liquidity levels. Read: Confused on How to Invest in ETFs? We Have Some Tips! Further read: 6 Reasons to look at ETFs