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Oil and Gas Accounting Software

Oil and Gas Accounting Software

Oil and gas accounting software for upstream, midstream, downstream and trading or ETRM delves into asset acquisition, exploration, development, production, transportation, storing, processing, and financial mark-to-market and hedge accounting.  It also tracks oil and gas projects, land leases, and production leases (first purchaser) while keeping records of all money-related items from all departments.

As a result of this, a good number of business software companies such as EnHelix has been established and they’ve played a great role in the advancement and growth of most energy companies. 

accounting software for oil and gas companies

Accounting software for oil and gas companies

Oil and gas accounting software like EnHelix accounting solutions designed specifically for the oil and gas industry to streamline accounting and provide automation and tools that are tailored to each segment of the oil and gas businesses. Imagine, the amount of data that goes through your accounting departments and thousands of transactions to account for, only a robust accounting software like EnHelix with reporting tools and artificial intelligence capability can automate, aggregate and analyze each of them promptly to close the book on time.

EnHelix is an integrated oil and gas software for commercial, operations, and accounting that eliminates data hand-off between different systems and save time on reconciliations to meet the tight deadline. Also, EnHelix new artificial intelligence solutions help accountants close their book faster by predicting accounting mistakes before they become real problems during the accounting close period.

For upstream oil and gas accounting, EnHelix provides production, financial and tax accounting solutions. For midstream oil and gas accounting, EnHelix provides robust volume accounting and plant owners accounting. Downstream accounting includes cost and financial accounting. Commodity trading accounting solutions include mark-to-marketing and hedge accounting.

Besides the core solutions, EnHelix oil and gas artificial intelligence automatically machine learns about your business data and provide an intelligent business dashboard with vital AI statistics and PKI.

oil and gas accounting software

 

Oil and gas accounting software with EnHelix artificial intelligence

Artificial intelligence is the ability of a machine to imitate intelligent human behavior. This technology comprises of machine learning (ML) which gives computers the ability to “learn” frequently from data without being clearly programmed. Deep learning is a branch of machine learning that uses algorithms called artificial neural networks (ANNs), which are driven by human intelligence and are capable of self-learning. These artificial neural networks are adapted to “learn” models and patterns instead of being explicitly programmed to resolve a problem. 

Although deep learning, the state-of-the-art method to AI across computer vision, natural language processing, and machine translation, has become prominent just recently, it’s needed for companies that want to go deep in AI. These algorithms are particularly good at identifying different patterns across noisy data, data that was once totally opaque to machines or both. 

EnHelix uses machine learning, deep learning, and even cognitive AI throughout its platform enabling companies to fully utilize AI for their energy business. This enables these companies to solve some of their problems without wasting time. In other words, instead of a human, we let the algorithm decide what’s important, to solve a problem. This approach makes things easier for the system and allows the data to make decisions. Most essentially, it reduces the potential for people to make mistakes or introduce their own biases. Goals won’t be achieved if you don’t use this approach, thus, limiting the end-user experience. 

Even though a custom deep learning set up can offer significant values and have the ability to provide more accurate results, building one comes along with unique defies.

They include;
•    New methods to model interpretability
•    Automation while testing, choosing, and promoting deep learning models
•    Specialized deep learning software and hardware needs such as GPUs and CPUs
•    Challenges and requirements for deep learning in production
•    Concerns for creating a data platform that can support deep learning
•    The need for enterprise-grade expertise

In summary, deep learning is that part of AI that has drawn deeply on our knowledge of applied mathematics, statistics, and the human brain. Deep learning is now set and ready to change enterprises. Because of its usefulness, it has gained a lot of popularity. So, do not be scared of using it responsibly, but a wrong adoption might lead to data having biases which will affect your business and the end users negatively. 

Deep learning can help get humans off the machine learning loop, hence, reducing the potential for biases in your system. In any case, it is always important to act ethically when creating any machine learning system.