BigDataScalability.com – Data is an important part of the oil and gas industry. Companies in the industry have been collecting, storing, and processing data. They use data as the core of their operations. It comes as no surprise if big data in oil and gas has many uses and benefits.
Regardless of the industry, big data is useful. A company that leverages big data can gain actionable insights that will help in making better, more actionable decisions.
The question is, how does big data help in the oil and gas industry? Also, what kinds of benefits oil and gas companies can derive from leveraging big data? Below, we explain what big data is briefly, how it helps the industry, its benefits, and its challenges.
Table of Contents
What Is Big Data?
Before we delve into big data in oil and gas, let’s get to know about big data first. The term “big data” refers to the vast amounts of data that can’t be stored and processed by using traditional methods and tools. Due to the sheer size and complexity, it is not until recent times that big data becomes a thing.
This owes to the advance in technology, which enables us to store and process vast amounts of data. Big data is not just about size and complexity, however. It is also about speed, variety, quality, and value.
The 5 V’s of Big Data
1. Volume
The first characteristic of big data is volume. It represents the volume or size of collected data. Currently, big data is measured in petabytes and even exabytes. To give a perspective, one petabyte is equal to 1,024 terabytes while one exabyte is equal to 1,024 petabytes.
It’s important to note that the volumes of data that we generate grow exponentially. It won’t be long before we see even larger data.
2. Velocity
The second characteristic is velocity or speed. Velocity refers to the rate at which collected data is generated and processed. Speed is important because the faster the data is generated and processed, the faster we can gain insights from it.
3. Variety
The third characteristic of big data is variety. Data is far from uniform as it comes in multiple forms. Data can be categorized into three forms: structured, semi-structured, and unstructured.
4. Veracity
The next V is veracity, which represents the quality of data. Not all data is equal. Some have good quality, some don’t. To make the most of big data, we must be able to distinguish and filter data. It is only by using data with quality that we can gain actionable insights.
5. Value
Lastly, value. Value refers to the usefulness of collected data i.e. the value it can provide. Note that what might be valuable data for one company might not be so for another. The value of data is largely determined by what the company can do with it.
Big Data in Oil and Gas Industry: How Does It Help?
Big data helps oil and gas companies in many ways. From ensuring human safety and reducing production costs, to upstream, midstream, and downstream optimization.
Ensuring Human Safety
One of the most important applications of big data in oil and gas is to ensure human safety. The safety of employees and the environment is one of the utmost concerns in the oil and gas industry.
When a company extracts its employees, there is always the risk of hazardous fumes affecting them. Companies can avoid this by leveraging big data to locate new sources of oil and gas. No potentially dangerous procedures are involved.
Reducing Production Costs
Many factors, both internal and external, affect the production costs of oil and gas companies. Oil drilling, particularly, is a very expensive process. With big data at their disposal, companies can improve production efficiency to reduce production costs.
Preventive and Predictive Maintenance
The next one is preventive and predictive maintenance. Using big data predictive analysis, oil and gas companies can create simulations to forecast maintenance occurrences.
Note that preventive maintenance is necessary because it reduces the expense of downtime and unpredictable reactive maintenance.
The forecasts can help companies to stay ahead by optimizing downtimes for large-scale maintenance operations.
Besides predictive maintenance, companies can also use big data to develop a precautionary maintenance strategy that involves regular equipment examination and replacement.
Upstream, Midstream, and Downstream Optimization
Upstream
In the upstream sector, companies can use big data to
- Manage seismic data
The upstream big data analytics begins with the collection of seismic data through sensors over a potential region of interest in oil exploration. After the data has been collected, the company then processes and evaluates a drilling location.
- Optimize drilling processes
Big data is well-known for its ability to predict what may take place in the future. Big data in oil and gas can be used to build predictive models to predict potential failures in machines.
Machines are equipped with sensors that collect data during operations. The collected data is then analyzed to find patterns and determine usage that is likely to cause breakdowns.
- Improve reservoir engineering
Downhole sensors, such as temperature sensors and pressure sensors, can be utilized to collect necessary data to improve reservoir production.
For example, using big data analytics, companies can develop reservoir management applications to get actionable and timely insights into temperature, flow, changes in pressure, etc. to improve reservoir engineering and profitability.
Midstream
Logistics in the oil and gas industry is very complex. The main concern is to transport oil and gas with minimum risk. To ensure the safety of logistics, companies use sensor analytics.
They use predictive maintenance software to analyze collected data to detect abnormalities (seismic ground movements, fatigue cracks, stress, corrosion, and so on). This, in turn, enables them to prevent accidents.
Downstream
In the downstream sector, oil and gas companies can utilize big data to reduce maintenance costs and minimize downtimes of equipment. With big data, companies can analyze the performance of equipment by comparing past and current data.
Benefits of Big Data in Oil and Gas
Adopting big data brings a lot of benefits for oil and gas companies. The following are some examples of the benefit of big data in oil and gas.
Highly Cost-effective and In Real-time
The oil and gas industry generates data at a very high speed on day to day basis. However, the volumes of data are not the only concern here. There is also the handling of vast amounts of data.
Traditionally, these are very costly for oil and gas companies. Of course, such costly endeavors impact the companies’ financial performance significantly.
This is where big data can help. Leveraging big data, oil and gas companies can not only reduce costs but also gather massive data in real-time. The use of big data analytics can help companies improve their production by 6 to 8 percent.
While the benefit for production is significant, the role of big data in oil and gas goes beyond efficiency. Near-real-time data visualization and alerts as well as storage of vast amounts of data sets are considered the most important benefits of adopting big data in oil and gas.
Better Decision-making and Reduce Risk
With big data at their disposal, companies are better equipped to make decisions. Big data provides companies with actionable insights, which translates to better decision-making.
Everything has a risk, especially the oil and gas industry. Companies must be able to manage risks as best they can.
For example, layers of rocks are different from one region to another. Lessons that a company learned from one area can be applied to areas with similar properties.
Using big data, the company can not only reduce risk in their operations but also learn lessons from their previous actions and each subsystem they encounter.
High Accuracy in Oil Exploration and Drilling Methods
Accuracy is indispensable in the oil and gas industry, especially when it comes to oil exploration and drilling methods. High accuracy can only be achieved by using data. This is where big data in oil and gas can help.
Oil drilling is very expensive. No company wants to look for oil in the wrong place. Companies can leverage big data to avoid this issue altogether. Using big data, they can have a more accurate idea of what lies underneath, thus saving a significant amount of time and effort.
From big data analytics companies can gain insights into how to optimize the subsurface mapping of the drilling locations, precise drill bit control (where and how to steer it), identify the best method to stimulate the shale oil, and so on.
Ensures Efficient Machines Performance
Machines are very important parts of the oil and gas industry. In oil drilling, for example, machines must work for many hours on end under severe conditions and temperatures.
To get the best outcomes, companies must ensure that their machines are in top condition and perform as they should. This can be accomplished by using big data in oil and gas. Utilizing big data, companies can ensure that their machines are working properly and not damaged due to failures or breakdowns.
Machines are equipped with sensors that gather data about their performance. The collected data is then compared to the aggregated data. This, in turn, ensures that downtime is minimized and parts that need to be replaced are replaced efficiently. Ultimately, this reduces additional expenses.
Challenges of Implementing Big Data in Oil and Gas
Big data has many practical applications in the oil and gas industry. It offers many benefits as well. However, as good as it is, big data in oil and gas does come with challenges. If oil and gas companies want to make the most of it, they must be able to overcome the challenges.
The challenges of implementing big data in the industry include
- Oil and gas companies must be able to conduct data transmission from the field to the data processing plants and do so according to the type of data, the volume of data, and data protocols. Not only that, but there is also a concern about the quality and frequency of the data gathered.
- In other industries, data scientists can work on their own to gain actionable insights from big data. However, the same can’t be said about the oil and gas industry. Due to the physics of the situation, data scientists need to work with expert oil engineers to make the most of big data in oil and gas.
- To leverage big data, oil and gas companies must have experts who specialize in computer technology, cloud technologies, open-source models, as well as iterative methods for development. These specific skill sets are indispensable.
Big data helps the oil and gas industry in more ways than one. From ensuring human safety and reducing costs to optimizations in upstream, midstream, and downstream sectors.
Big data in oil and gas also brings a lot of benefits. Of course, there are also challenges that companies must overcome if they want to make the most of big data. Since big data isn’t a passing trend, companies must be able to not just adapt but also leverage it so they can gain a competitive edge.
