Top 7 Digital Technologies Transforming Oil & Gas Operations

8 min read

“Data is the new fuel”, this quote best suits every industry on earth, trying to reach the ultimate objectives of increased utilization of equipment, reduced NPT & optimization of the operations. Talking about the real-life scenarios of operators there on the field, they are trying their best to produce last bit of oil and gas from the subsurface in order to manage profits with their OPEX. While achieving this, they are encountering various challenges on the field on a day-to-day basis, where AI is posing as a remedy for all their challenges.

Talking about the stimulus for the oil and gas transformation, the trends of the ageing workforce, extreme price pressure persisting after the great downfall of oil prices & accelerated asset digitization are pushing this industry more towards data-driven solutions. With every granular information of the operations stored in the form of data lakes, more insights are derived from that leading to more efficient operations done by the operators. 
Features like remote monitoring are already trending across oil & gas stakeholders, but digital twin, remote Anomaly Detection, prediction, automation, chatbots, AR/VR & video analytics are proving to be the real game changer. We will go one by one in this post to make you understand as to how these features are implemented across the producing fields.

  • Digital Twin
Operators on the producing field monitor the overall performance of the equipment, such as compressors, separators, etc. with the help of the parameters present at different subsystems. But how do they map the failures or issues to a particular subsystem, when talking about any maintenance activity? Take an example of a compressor which has different systems inside it, bearing housing, rotor, D.C. motor, etc. But what if the efficiency of the compressor is declining, reason being the driving voltage fluctuations, how would the operator be able to detect it?

Here, Digital Twin will come into picture which helps produce a replica of the equipment deployed over the field. Being a virtual model, this technology helps in analysing the data by acting as a platform to check the performance of the equipment beforehand to develop a solution for potential problems. Considering the situation of the reduced efficiency of the compressor, the operator can directly view that the subsystem, D.C. motor is facing the issue. Thus, it will be easy for the field operator to plan the next steps in order to increase the compressor performance.
 
  • Anomaly Detection
Consider an operator on producing field managing equipment like compressors, storage tanks, etc., recording load of data from the sensors in the form of data lakes. But detecting anomalies is too difficult with the naked eye by just viewing the data. Over 2 million sensors installed over the field, recording data every second, it will be next to impossible for the field engineer to detect anomaly in one equipment or operation as to how well it is performing.

As a helping hand to him/her, this remote anomaly detection, running on first principle models & statistical algorithms, will detect the anomalies in the data like wellhead pressure crossing the threshold limit, which can lead to events of damage to choke line or might lead to spillages or leakages. Even detection of a small variation is easily possible in this feature while sitting in the operations command centre.
 
  • Prediction
With diagnostics feature, the field engineer will be notified of the anomalies in the data, but all this analysis will be after the data has been recorded. How about some indications what might occur in the next 60 minutes? Or how long till a compressor fails? This is all made possible by the machine learning models & regression analysis running behind the model helping the field engineers take a decision keeping in mind the possible event in the near future with some confidence score. 

Consider the situation, when the compressor is working on the gas producing field running on the discharge pressure of more than 18,000 psi in order to send the gas to the gathering stations. But after some time, the pressure keeps on declining by 1000 psi, the diagnostics will show that the pressure is low, but the prediction feature will give an insight that if this situation persists, within 3 days the compressor will fail with 80% confidence. 
The confidence will be based on the amount of data & the health of the compressor. Also, this feature will enable the engineers with predictive maintenance, which will give information as to when the next maintenance should be done, according to its performance, irrespective of the scheduled maintenance date.
 
  • Automation
While considering a producing field, diagnostics & prediction can create new opportunities in order to reduce the loss of production & increase equipment uptime. But how about the situation where an operator must travel to the producing field in order to change the parameter of equipment. For example, if the production flow is low at the inlet of the separator, the field operator will visit the producing field in order to open the LCV, present before the separator, which will be the solution provided by the RCA analysis from the diagnostics, thus wasting time.

The feature of automation basically means to close the loop of the operation, in order to apply the suggestion or the prediction in order to reduce the loss of time & production. As of the example given above, time will be wasted while reaching the LCV. But if automation is there in play, the result of RCA will be taken automatically by the system, thus itself opening the LCV which will help control the situation.
 
  • AR/VR
The field operators are given ample proper training before they are handed over the safety hat to be there on the producing field. But how to make them more prepared about the situations like that of spillage by making them analyse it in person? Or imagine the situation where the field technician is facing a situation where equipment, like a separator, is not working effectively, as the separated water flowline from the separator is having oil more than 10%? Due to less experience in the field, the technician contacts his operations manager, & the manager sends out the expert technician to the field. But this whole process takes about 4-5 hours. How this time can be saved?

Here, Virtual Reality (VR) & Augmented Reality (AR) plays an important role. VR helps the operators train the oil and gas personnel by keeping them in real life situations and AR helps the manager to view the equipment in real time in the operations command centre. So how will these features be a game changer? In VR, they will witness how the situation will be like in the training rooms, instead of just reading off in some books or watching a video. Same goes with familiarizing them with the facilities before physically going there so that they will be having an idea of all the equipment there on the field & how to operate them effectively. In AR, both the field technician & the manager will wear head-mounted devices & using the video telecasted by the technician’s mount, the manager will be able to see the equipment in real time as if he/she is there, thus guiding the technician on how to manage the situation in real time, thus saving those 4-5 hours of travel!
 
  • Chatbots
How often Google Assistant or Siri is used if any person has a question? Guess most of the time, right. It is so simple now to ask the voice assistant, what is the weather in Illinois, or will it rain or not. So how about inculcating the same principle here, in the production phase of the upstream? 

Just think as to how the Chatbots will revolutionize the upstream production. First, what is a chatbot? A chatbot is nothing but a toll of AI where you can interact with a mobile application, to get the answers to questions, like how many NPT events have occurred in the field yesterday, or when is the next maintenance check scheduled for the separator id “123”. It will directly be connected to the platform so it can retrieve the result easily. All you need is an internet connection! 

So, with this tool, instead of looking into the dashboard for the results after going through some steps, the operator can directly interact with the chatbot by typing the question & it will give you the result. So simple, right?
 
  • Video Analytics
Talking about the last of the AI use cases, it is a common sight video camera installed inside the banks which can detect motions at the night when the bank is closed? And it is considered the innovation of the decade. Similarly, there is an innovation introduced in the Oil and Gas industry. So, what is it?

There is a feature of video analytics of AI which can be applied to any normal video cameras installed across the producing fields. But how will it work? Just like the analogy of the situation of theft, the video cameras can detect the field personnel who are not wearing the PPE like hard hats, earmuffs, etc. or there is the presence of humans in the red zone areas, where no human should go. 
So, when video feed is checked, it will show the footages where these all restrictions are not obeyed. This feature will help the operators maintain the necessary awareness about the HSE norms over the producing field.

Closing Thoughts

According to us, these are some of the AI use cases which will surely create safety across the fields & also help increase the efficiency of the operations, thus increased productivity. Some of these features are already applied with others getting introduced slowly. These features suggest as to how important digitization can be to oil and gas industry which is quite evident with the fact that by 2021, the investment into digitization by this industry will be a whopping $52 Billion!

With Cerebra already rolling out all these features for the operators, do you want your operations & equipment to help you save millions & create a safe environment for the field personnel to work? Contact us today to experience the AI in action!
Hope you liked this post on how different features are helping production phase of upstream. Do let us know your views in comments & share it! Stay tuned for the next post where we will help you understand why early leak detection might be next feature that you would want to have it by your side.


Derick Jose

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