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SLB Machine Learning Innovation Competition 2023

February - June 2023

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SLB Machine Learning Innovation Competition 2023

We are excited to announce a new initiative by D&I EAG – SLB Machine Learning Innovation Competition 2023!

This competition is open to students & professionals residing in Malaysia and intended to provide a platform for bright minds to unleash their potential and to showcase our Data Science and Innovation vision throughout the nation. This is an event that comprises of 3 different parallel competitions.

This event will be open for registration to students & professionals (external*) from 10th Feb – 10th Mar 2023.

*Participation should not include personnel from service companies including SLB.

DELFI | Data Science Competition

DELFI | Data Science Competition

Team Composition Register here:
Team Composition

3 University Students/Graduates +1 Professional

 Register here:

DELFI Data Science Competition Registration Link
  • Student should register per team and professional must register individually
  • Do not have enough team member? Refer Team Composition
  • Participants should agree on the Terms & Conditions applied upon registration

Timeline

 ML Innovation Competition-2023-DELFI-timeline

 

Prizes

 DELFI Data Science Competition prizes

 

Eligibility Criteria

 
Students, Fresh Graduates & Young Professionals
Students, Fresh Graduates & Young Professionals Students, Fresh Graduates & Young Professionals Students
  • Currently enrolled in any universities/institutions in Malaysia
  • Enrolled in a Diploma, Bachelor, Master's, or Doctoral program
  • Completed at least two semesters of study for Diploma/Bachelor degree students or with less than three years of work experience for Master's/Doctoral program
  • Preferred majors:
    • Earth Sciences: Geology, Geophysics
    • Engineering: Petroleum Engineering, Chemical Engineering
    • IT: Mathematics, Information Engineering, Computer Science, Computer Engineering
    • Others: Mechanical Engineering, Electrical Engineering, Industrial Engineering

Fresh Graduates
Graduated 2 years (max.) after graduation by the time of registration from any universities/institutions in Malaysia

Young Professionals (YPs)
  • Less than 3 years of experience in the industry (If >3 years, participant should enroll as a professional)
  • Industry of work is not limited, however, must not be employed by an oilfield/geothermal service company
Important Note:
  • A "Students/Fresh Graduates & YPs" team that does not have any member from IT background, must have programming capabilities such as programming language proficiency, Artificial Intelligence/Machine Learning, and visualization.
  • All entries - IP become the property of SLB.
 
Professionals
Professionals
  • A professional should be employed in an oilfield/geothermal operator companies
  • A professional should be residing in Malaysia
  • A professional from service company is not eligible (including SLB personnel)
  • Required to register using official business email address
  • A professional should have min. 3 years of experience
  • A professional will register as an individual.
  • A professional is not required to have programming skills, however, having familiarity to machine learning or programming language is a plus.

Team Composition

 DELFI Data Science Competition team compostion

 

Stage 1: Proposal [28 Mar – 11 Apr]

 ML Innovation Competition-2023- DELFI proposal

 

Problem Statement

  • Problem Statement Challenges List will be announced to the participants on 28 Mar.
  • Participants can also propose their own problem statement respective to each domain
 ML Innovation Competition-2023- DELFI problem statement

 

Stage 1: Proposal Evaluation Criteria

 
Category Evaluation Criteria Descriptions Weighting
Category Objectives Evaluation Criteria Identification of Problem Domain Descriptions
  • Providing a comprehensive project background.
  • Objectives are well-defined and articulated.
Weighting 10%
Category Awareness Evaluation Criteria Feasibility Study Descriptions
  • Detailed and extensive explanation of the specifications and the limitations of the existing systems.
Weighting 5%
Category Creativity Evaluation Criteria Originality/ Innovation Descriptions
  • Strategy to tackle the industry challenges- from innovative perspective and/or using new methods
 Weighting 10%
Category, Category Methodology & Technical Solution  Evaluation Criteria Technical Solution Descriptions
  • Complete explanation of the key concepts.
  • Strong description of the technical requirements of the project.
  • Input data, data source, and data size
  • Workflow on data preprocessing
  • Feature engineering
 Weighting 30%
Evaluation Criteria Methodology & Technical Solution Descriptions Solution Architecture Weighting
  • Machine Learning solution- selected algorithm and why
  • Post processing (optional)
  • Evaluation metrics (how participants evaluate the result)
 25%
Value Creation Impact/ Value Added
  • Solution answers the challenge posed and potentially improves a current situation and offers a game changer
15%
Conclusion Conclusion and Discussion
  • Expected results are presented in very appropriate manner. Project work is well summarized and concluded.
5%
Bonus Point  Technical Scalability
  • Potential for growth and scalability - solutions provide a broad application
 5%
ML Poster Competition

ML Poster Competition

Open to: Theme:
  1. Students
  2. Professionals (Digital Players, Operators)

Note: Participants can join as an individual or in a team (Max. 3 members)

*The Application of Machine Learning, Data Science and Artificial Intelligence in the Oil and Gas Industry"

Register here:
ML Poster Competition Registration Link

Participants should agree on the Terms & Conditions applied upon registration

 

Timeline

 ML Innovation Competition-2023- Poster timeline

 

Prizes

 Machine Learning Innovation Competition 2023 prizes

 

Eligibility Criteria

Students

Each team consists of members from the same university and one person can only become a member of one team.
Professionals
  1. Open for Digital Player, Operators Personnel
  2. Not opening submission for Service Company Employees including SLB employees
General Criteria
  1. Participants must be residing in Malaysia
  2. Each team consists of an individual or maximum 3 members.
  3. All submissions shall not be published previously in professional journal/been used in other regional/international competitions.
  4. Plagiarism is not tolerated, and any indication of plagiarism will be disqualified immediately.
  5. Participants are responsible for and shall bear any additional costs or expenses associated with preparing and submitting the poster.
  6. Participants assume all risk for damaged, lost, late, incomplete, invalid, incorrect or misdirected content.
  7. Fail to obey the rules, format or late submission may receive 10% points deduction or disqualification.
Rights
  1. Entry in the contest constitutes full permission to publish names and photos of winners without further compensation.
  2. The determination of eligibility of entries and any interpretation of these rules is at the sole discretion of SLB and shall be final and binding upon all participants.
  3. By participating, the participants agree to abide by and be bound by terms and conditions applied upon registration

Poster Requirement & Format

Requirement
  • Each team must submit Machine Learning Poster Competition Entry Form.
  • Must address the theme: "The Application of Machine Learning, Data Science and Artificial Intelligence in the Oil and Gas Industry".
  • Electronic poster submission shall be made via by the deadline on 3rd April.
  • All information presented in the poster must be cited, giving credit to the original source.
  • Any topic is permissible, but poster must illustrate clear introduction, abstract, methodology, result, conclusion and necessary diagrams or supporting illustrations.
  • " No trademarked/ copyrighted images or phrases should be used.
Format
  • Participants can refer to the provided poster template in the registration link as a guideline - this template is a best practice guideline, please do not limit your creativity. 
  • Theme of the poster must follow SLB's branding guideline including logo and tagline.
  • Ratio of poster (Microsoft PowerPoint) is 9:16
  • Design and organization are all based on participants.
  • Poster orientation must be in Portrait.
  • Maximum number of pages are two (2).
  • Content should be in English.
  • Font size must be readable from a distance.
  • Poster with any form of potentially offensive material or otherwise inappropriate for public display will be disqualified.
  • Reference must follow Harvard Citation Format.
  • Electronic submissions are made via SharePoint adhering to the following instructions:
    • Maximum file size is 100 Megabytes (MB)
    • Preferred file type is pdf
    • Team is responsible to make sure poster can be viewed for judging via the file.

Poster Evaluation Criteria

Category Description Weighting
Coverage of Topic

Details on poster capture the key message about the topic and increase audiences's understanding

 30%
Organization

Information is organized with clear titles and subheadings.

 5%
Graphics

All graphics are related to the topic and make it easier to understand.

 5%
Labels   

All items of importance on the poster are clearly labeled with labels that can be read.

 5%
Attractiveness  

Exceptionally attractive in terms of design, layout and neatness.

 10%
Sources  

All sources (information and graphics) have citation and accurately documented.

 5%
Mechanics  

No grammatical or punctuation errors.

 15%
Presentation  
  • Accurately answer all questions related to facts in the poster and processes used to create the poster.
  • Stayed within the time limit and did not seem hurried or too slow.
35%

 

ML Video Competition

ML Video Competition

 
Open to: Theme:
Open to:
  1. Students
  2. Fresh Graduates
 Theme:

"The Future of Machine Learning and its Value to the Community"

Register here:
ML Video Competition Registration Link

Participants should agree on the Terms & Conditions applied upon registration

Timeline

 ML Innovation Competition-2023- Poster timeline

 

Prizes

 Machine Learning Innovation Competition 2023 prizes

 

Eligibility Criteria

 
Rules and Eligibility
Rules and Eligibility
  • Open to all university students, graduates residing in Malaysia
  • Entry can be as an individual or a team (maximum 3 people).
  • One individual/ team can only submit ONE entry.
  • One person can only participate in ONE team.
  • Plagiarism of any kind will result in disqualification.
  • Must be original content authored, composed, and performed by students/graduates identified in the entry form as participants.
  • No professional (paid) assistance may be used in production of the video. Any entry doing so may be disqualified.
  • Participants are responsible for and shall bear any additional costs or expenses associated with preparing and submitting the poster.
  • Participants assume all risk for damaged, lost, late, incomplete, invalid, incorrect or misdirected content.
  • SLB does not assume responsibility or liability for any video or portion thereof, or for any claims, damages, or losses resulting from the use or dissemination of any video submitted in this contest.
.

Requirement & Format

 
Requirement
Requirement
  • Video must be 30s- 1 min long.
  • All entries must be in English.
  • Must address the theme: "The Future of Machine Learning and its Value to the Community".
  • Must be appropriate for viewing by the general public and by a multi-cultural international community.
  • All information presented in the video must be cited, giving credit to the original source.
  • No copyrighted materials (music, images, video clips etc.) unless you own the copyright or have license.
  • Upload the video in Instagram/LinkedIn/TikTok (Minimum 1 platform)
  • Upon submitting to social media before 1st June, all submission should also be submitted via SharePoint. Link will be shared with registered participants. Put hashtag #SLBMLCompetition2023 #SLB 
 
Format
Format
  • Videos must be either mov or mp4 format.?
  • No larger than 1 GB.
  • Must begin with a 5 second of title screen that includes following information:
    • Name of participants
    • University
    • Title of video
  • Video duration (max. 1 min) will not include the 5 second title screen.

Evaluation Criteria

Category Description Weighting
Content 
  • Does the video address the theme of the contest?
  • Is the information clear and well expressed?
  • Does the video run within the 1-min time limit?
  • Are there any copyrighted materials used in the video?
  • Is any portion of the video inappropriate?
 30%
Creativity
  • Is there unexpected or innovative use of video that enhanced the power of the video’s message?
  • Is the information clear and well expressed?
  • Does the message provide a new perspective? 
  • Does the total video presentation display a combined innovative use of design, materials, and ideas?
15%
Overall Effectiveness of Delivery
  • Is there one key message that is clearly stated? 
  • How engaging is the message?
  • Is the viewer compelled to keep watching?  
20%
Technical Quality of Video
  • Lighting, Sound, Editing (poor sound quality can adversely affect all other judging criteria)
25%
Social media engagement
  • High engagement earns extra points (Likes, reshare, repost)
10%
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