SEG/SPE Workshop: Fibre for the Future: AI-Driven Intelligence for Exploration, Production & Development

21–22 July 2026
Kuala Lumpur, Malaysia

Fibre‑optic sensing has rapidly evolved into a transformative technology for exploration, development, and production. Its ability to deliver continuous, high-resolution measurements of temperature, acoustics, and strain enables operators to monitor wells, reservoirs, and infrastructure with unprecedented detail. May it be DTS, DAS or DSS, combining fibre‑optic data with advanced analytics and AI is unlocking new levels of insight and operational efficiency across the energy sector.

In exploration, distributed acoustic sensing (DAS) supports dense seismic acquisition while reducing on-site logistics. Machine learning enhances this workflow through automated event screening, noise characterization, and scalable quality control, all while maintaining compatibility with standard seismic processing and inversion practices. In development, distributed sensing is now a key tool for hydraulic‑fracture diagnostics and reservoir characterisation. Continuous measurements help operators evaluate fracture initiation, treatment effectiveness, and evolving fluid behaviour, while predictive analytics extract repeatable patterns that support performance benchmarking across stages and wells.

Operational deployment has also advanced significantly. Integrating fibre optics into conventional conveyance tools such as slickline, e-line, and coiled tubing has expanded access to existing wells while reducing the technical and economic constraints of permanent installations. Emerging deployment methods—such as dissolvable carriers and gravity‑dropped bare fibre—have further improved efficiency by eliminating the need for conveyance cables and lowering logging costs.

Technical Committee

Committee Co-Chairs:

• Arief Budiman B. Hermani, PETRONAS
• Sarvagya Parashar, Halliburton

Committee Advisor:

• Ts. Shahril Ridzauddin Mohd Mokhtar, PETRONAS

Committee:

• Amir Ghaderi, SINTEF
• Artur Giniyatullin, TGT Diagnostics
• Bamidele Abdulhakeem Adeniyi, Universiti Teknologi PETRONAS
• Harrison Moore, Shearwater
• Jauhari Tahir Bin Khairuddin, FPT Corporation
• Kittinat Taweesintananon, PTTEP
• Markus Chin, Halliburton
• Michel LeBlanc, Halliburton
• Mikko Jaaskelainen, Halliburton
• Mustafa Qizilbash, YPT
• Nurul Nadzirah A Rahman, PETRONAS
• Omar Saad, King Abdullah University of Science and Technology (KAUST)
• Ong Kok Kheong, Tendrill
• Peng Guo, CSIRO
• Ran Bachrach, SLB
• Shamsul Shukri, PETRONAS
• Sukhveender Singh, PETRONAS
• Takao Nibe, JAPEX

Contact

Intan Bhaizura
SEG Asia Pacific
Email: [email protected]

Workshop Themes

The workshop will be structured around several thematic areas such as:

• AI-Enhanced Exploration: From DAS Seismic to Subsurface Modelling

Exploration budgets are constrained, and success depends on faster, more reliable subsurface understanding. DAS-enabled seismic, combined with AI, accelerates interpretation. We are looking for papers that explore:

• Dense seismic sampling using surface DAS
• Improved imaging beneath complex overburden
• AI-assisted seismic interpretation and attribute extraction
• Faster prospect evaluation and uncertainty reduction

• Fibre Optic Streamers for High-Resolution Seismic Imaging

• Fracture Monitoring & Unconventional Applications

Unconventional reservoirs remain a cornerstone of global oil and gas supply. Distributed Acoustic Sensing (DAS), combined with AI-driven analytics, has fundamentally changed how operators understand hydraulic fracture behaviour in real time. We are looking for papers that explore:

• Enables stage-by-stage fracture diagnostics
• Identifies cluster efficiency, fracture-driven interactions (FDI), and SRV
• Supports completion optimization and well spacing decisions
• Directly links subsurface monitoring to production outcomes and EUR

• Intelligent Production: Optimisation and Autonomous Operations

The industry is transitioning from reactive to predictive and autonomous operations. Fibre optics provides the continuous data stream required to enable this shift. We are looking for papers that explore:

• Real-time flow monitoring using DAS/DTS
• Early detection of water/gas breakthrough
• AI-driven optimization of artificial lift and choke settings
• Supports smart fields and digital twin initiatives

• Microseismic applications in hydraulic fracturing, reservoir injection & integrity monitoring

• Real Time Data Processing for Distributed Fibre Optic

Data volume presents a significant challenge for the application of distributed fibre-optic technologies (DAS, DTS, DSS, etc.), with a standard DAS deployment generating tens of terabytes of data during a single monitoring period. Real-time processing systems enable on-site data handling, extracting actionable information for well monitoring and integrating DAS with other real-time measurements such as DTS and DSS. 

• Software Processing & AI Interpretation of Fibre Data

Fibre-optic sensing produces massive, high-frequency datasets. Without advanced processing and AI, the value of DAS/DTS/DSS cannot be realized at scale.

• Converts raw fibre signals into actionable subsurface intelligence
• Enables real-time monitoring and decision-making
• Supports automated event detection, classification, and alerting
• Critical for moving from pilot projects to field-wide deployments

• Time-Lapse Seismic and Reservoir Characterization Using DAS 

Time-lapse (4D) seismic remains one of the most powerful tools for reservoir management. Fibre-enabled DAS allows cost-effective, permanent monitoring that was previously impractical.

• Continuous monitoring of fluid movement and pressure changes
• Enables field-wide surveillance at reduced cost – 
• Improves reservoir models and recovery strategies
• Particularly impactful in offshore and mature fields

• Well Integrity Monitoring Using Fibre Optics

As wells age and operating envelopes expand (HPHT, unconventional, CCUS), well integrity has become a top operational and regulatory concern.

• Continuous monitoring of leaks, casing deformation, and barrier performance
• Reduces reliance on periodic intervention-based diagnostics
• Improves HSE outcomes and regulatory compliance
• Extends asset life and reduces abandonment risk

Registration Information

Early Bird Registration Fee (must be registered and paid before 20 June 2026)
US$1,100(Member) | US$1,300 (Non-member)

Full Registration Fee (begins from 21 June 2026 onwards)
US$1,350 (Member) | US$1,550 (Non-member)

Academia Registration Fee
US$300(Member) | US$350 (Non-member)

Student Registration Fee
US$200 (Member) | US$300 (Non-member)

Who Should Attend?

This workshop brings together industry professionals and academics to share field learnings, highlight technological advancements, and identify outstanding challenges. Discussions will focus on integrating fibre‑optic sensing with geoscience workflows, developing scalable AI-driven monitoring solutions, and shaping best practices across the asset lifecycle—from exploration to production and beyond.