RPA for Estimating ER Releases

Introduction

In the oil & gas industry, estimating is a critical function that involves predicting the cost of a project accurately for planning and funding purposes. The process of estimating is complex and requires a significant amount of time and effort, as it involves analyzing different variables such as labor, materials, equipment, and other project related contributors. Occasionally, estimating engineers are required to produce multiple types of estimates that are often repetitive and high volume. The manual nature of the estimating process makes it prone to errors, which can lead to inaccurate cost predictions, project delays, and increased costs.

To overcome these challenges, companies have been exploring the use of RPA technology to automate repetitive and rule-based tasks associated with the estimating process. RPA is a technology that allows companies to automate repetitive tasks by using software robots that mimic human actions. These software robots can automate various tasks such as data entry, report generation, and other administrative tasks.

Within Saudi Aramco Estimating Services, one type of estimate that is commonly requested is the “onshore maintain potential expenditures request release” estimates, which is a time-sensitive expenditure request estimate that is developed by the proponent organization and submitted to the estimating organization for review and endorsement. These types of estimates are similar, repetitive, and high volume.

The workflow for developing and submitting these estimates is a multi-step process that involves several stakeholders. The proponent organization first develops the estimate and submits it to the estimating unit head who assigns the request to an estimating engineer. The estimating engineer assigned to the request then reviews the estimate and provides their endorsement. Data used in the estimation process is mostly derived from long-term agreements and some internal references. Once the estimate has been endorsed by the estimating engineer, it is submitted for approval by Estimating and Proponent Management.

Upon completion of the estimate, the estimating engineer compiles the estimate files per quality assurance and quality control (QA/QC) guidelines to maintain a record. This ensures that the estimate is accurate, reliable, and can be easily retrieved in the future if needed.

Robotic Process Automation (RPA)

Robotic Process Automation (RPA) is a software technology that mimics human interactions. Software robots—instead of people—do repetitive and lower-value work, like logging into applications and systems, moving files and folders, extracting, copying, and inserting data, filling in forms, and completing routine analyses and reports [1].

RPA has a wide range of applications across various industries. Some of the top applications of RPA include Healthcare, Banking, Human Resources, and Finance. In Healthcare, RPA can help with various levels of patient care. In Banking, RPA can help with multiple repetitive tasks that prioritize data accuracy. In Human Resources, RPA can help with tasks such as onboarding and payroll processing. In Finance, RPA can help with tasks such as account reconciliation and financial statement generation [2].

In general, RPA can be linked with Artificial Intelligence (AI) tools to provide some AI capabilities within the RPA process. However, RPA was not linked with any AI tool within the described use case.

Case Study

This case study focuses on the deployment of RPA technology on Maintain Potential ER Release Estimates.

Maintain Potential projects purpose is to sustain crude oil and gas production from onshore and offshore fields through constructing the well head tie-ins to the existing Saudi Aramco pipeline network. Onshore Maintain Potential is being funded through approved Expenditure Request (ER) Release Estimates where these are incremental funding mechanism, part of an approved yearly Master Appropriation plan, for well-defined scope of works which are routine and repetitive in nature.

Saudi Aramco Estimating Services had identified that the estimating process was time-consuming and prone to errors due to the repetitive nature of some of the tasks involved. To overcome these challenges, the company decided to implement RPA technology to automate the estimating process for the pure well tie-in for Onshore Maintain Potential ER Releases, where these are repetitive and high in volume.

The RPA implementation process involved the following steps:

1. Identification of the tasks to be automated: Upon understanding RPA technology capability and applicability, team scouted for tasks/estimates that are high in volume, repetitive and rule-based such as data entry, report generation, and other administrative tasks. We found that Onshore Maintain Potential ER Releases are the perfect fit for that technology.
2. Design and development of the RPA solution: The RPA solution was designed and developed by a team of RPA developers who worked closely with the estimating engineers to understand the requirements of the estimating process for the mentioned type of estimates. The RPA solution was designed to automate the identified estimate requests and was integrated with the company’s existing SAP interface for smoother processing. As described briefly in Figure 1 and in more details in Figure 2.
   
   ER Releases cost estimates, contains required costs for Oil, Gas and Water wells Tie-ins, which will be funded through final SAP output named ER Release 56D. Cost estimates are prepared by Proponent based on following documents/inputs: Company Estimate Request (CER) document, Survey document, CER file in the form of Excel spreadsheet with calculations and costs for Materials and Construction, Saudi Aramco Material System (SAMS) screenshots, Excel spreadsheets containing Work Unit Rate (WUR) database.
   
   Estimating Services Division responsibility is to review, validate and endorse funding ER Release 56D, based on above mentioned documents, plus an Excel interphase sheet.

3. Testing and validation: The RPA solution was tested and validated to ensure that it met the requirements of the estimating process. The testing phase involved the use of test cases to ensure that the RPA solution was accurate and reliable. We learned that the standardized submitted documents is crucial for the RPA solution to perform well. Additionally, RPA should be monitored for any exceptions or changes in the business rules.
4. Deployment and training: Once the RPA solution was tested and validated, it was deployed in the Estimating Services. The Estimating SMEs were trained to use the RPA solution.

The RPA implementation in the Estimating Services produced several benefits for Saudi Aramco, including:

1. Increased productivity: The RPA solution automated repetitive and rule-based tasks, which allowed the estimating engineers to focus on more critical tasks such as validation and analysis. This resulted in increased productivity, as the estimating engineers could produce estimates faster and maintaining the high accuracy.
2. Reduced processing time: The RPA solution reduced the processing time of the targeted type of estimates by automating them. This resulted in faster turnaround times for estimates, which improved the company’s overall efficiency.
   
   By comparing year-by-year Onshore Maintain Potential Budget Item (BI) estimate request completion durations, it was found that the year of 2022, where RPA was implemented, more requests are processed in addition to reducing the average processing time for each request. In 2022, RPA has processed more than 450 estimate requests this accounts for more than 20% of the total number of estimates issued by Estimating Services Division.
   
3. 24/7 robot estimator available: The RPA solution provided 24/7 availability of the robot estimator, which allowed the company to produce estimates around the clock. This was particularly beneficial for the company when working on projects with tight deadlines.
4. Consistent high accuracy: The RPA solution maintained a sustainable consistent high accuracy of estimates by reducing the likelihood of errors that can occur during the manual data entry process. This resulted in more accurate cost predictions, which reduced the risk of project delays and increased costs.
   
   Part of the RPA process is the exception validation and supervisor review & approval. Excluding the first batch of RPA-executed requests (piloting phase), performance of the processed requests is showing 100% processing rate, where all requests processed didn’t need to be changed by estimating SMEs.

Despite the benefits, there were also some challenges faced during the RPA implementation process. For instance, the scoping and design of the RPA solution was a challenging task. The solution involved more than 3000 steps and validations, which required us to detailed every single step that the RPA should replicate. This was necessary to ensure that the RPA could accurately process the targeted repetitive estimate requests.

Conclusion

This paper presents a case study of RPA implementation in the Estimating Services within Saudi Aramco, which led to increased productivity, reduced processing time, and 24/7 availability of the robot estimator. In 2022, RPA has processed more than 450 estimate requests accounting for more than 20% of the total number of estimates issued by Estimating Services Division.

The RPA implementation process involved the identification of the estimate types to be automated, the design and development of the RPA solution, testing and validation, and deployment and training. Overall, the RPA implementation in Saudi Aramco Estimating Services for Onshore Maintain Potential ER Release was a success, and the company is considering expanding the use of RPA technology to other areas of the business.

RPA capabilities can be potentially expanded to process the annual Capital Program estimate updates during Front End Loading (FEL) stages.

References

1. “What is Robotic Process Automation - RPA Software | UiPath,” UiPath. [Online]. Available: https://www.uipath.com/rpa/robotic-process-automation.
2. N. Ostdick, “The Evolution of Robotic Process Automation (RPA): Past … - UiPath,” UiPath Blog, 26-Jul-2016. [Online]. Available: https://www.uipath.com/blog/rpa/the-evolution-of-rpa-past-
   present-and-future.