Call for Paper Proposals

1.1 Basin Evolution and Petroleum Systems—Basin Architecture, Tectonics, and Petroleum Systems
1.2 Basin Evolution and Petroleum Systems—Source Rock Maturity, Migration, Charge, and Phase Risk
1.3 Basin Evolution and Petroleum Systems—Trap, Seal, and Containment Integrity
1.4 Basin Evolution and Petroleum Systems—Exploration Lessons Learned and Near-Misses
1.5 Seismic Acquisition, Processing, and Imaging—Land and Shallow-Water Seismic Acquisition
1.6 Seismic Acquisition, Processing and Imaging—Seismic Acquisition in Environmentally Constrained Settings
1.7 Seismic Acquisition, Processing and Imaging—Imaging Beneath Salt, Carbonates, and Complex Overburden
1.8 Seismic Acquisition, Processing and Imaging—Velocity Modelling, Depth Imaging, and Advanced Inversion
1.9 Seismic Acquisition, Processing, and Imaging—Reprocessing and Reinterpretation of Legacy Seismic
1.10 Integrated Exploration Workflows—Play-Based Exploration and Prospect Maturation
1.11 Integrated Exploration Workflows—Integrated Geology–Geophysics–Geochemistry Workflows
1.12 Integrated Exploration Workflows—Exploration in Mature and Underexplored Basins
1.13 Integrated Exploration Workflows—Portfolio Decision-Making Under Uncertainty
1.14 Digital, Data, and AI Applications in Exploration—AI-Assisted Interpretation, Prospect Screening, and Risking
1.15 Digital, Data, and AI Applications in Exploration—Data Integration and Conditioning of Legacy Datasets
1.16 Digital, Data, and AI Applications in Exploration—Accelerating Cycle Time from Data to Decision
1.17 Other

2.1 Static Reservoir Characterisation—Carbonate, Clastic, and Fractured Reservoir Heterogeneity
2.2 Static Reservoir Characterisation—Reservoir Characterisation in Giant, Laterally Extensive, and Multi-Contact Fields
2.3 Static Reservoir Characterisation—Facies Modelling, Rock Typing, and Connectivity
2.4 Static Reservoir Characterisation—Reservoir Quality Prediction and Uncertainty
2.5 Dynamic Modelling and Simulation—Full-Field Simulation of Mature and Complex Assets
2.6 Dynamic Modelling and Simulation—Naturally Fractured and Dual-Porosity Systems
2.7 Dynamic Modelling and Simulation—History Matching and Coupled Geomechanics
2.8 Dynamic Modelling and Simulation—Deep, HPHT, and Unconventional Reservoir Modelling
2.9 Reservoir Surveillance and Monitoring—Pressure, Production, Tracer, and 4D Surveillance
2.10 Reservoir Surveillance and Monitoring—Surveillance-Driven Optimisation and Uncertainty Management
2.11 Formation Evaluation, Petrophysics, and Rock/Fluid Properties—Open- and Cased-Hole Evaluation (LWD/MWD)
2.12 Formation Evaluation, Petrophysics, and Rock/Fluid Properties—Core, SCAL, PVT, and Rock–Fluid Characterisation
2.13 Formation Evaluation, Petrophysics, and Rock/Fluid Properties—Petrophysics in Complex and Low-Resistivity Reservoirs
2.14 Digital, Data, and AI Applications in Reservoir Engineering—AI-Assisted Characterisation and History Matching
2.15 Digital, Data, and AI Applications in Reservoir Engineering—Hybrid Physics–Data Modelling and Anomaly Detection
2.16 Digital, Data, and AI Applications in Reservoir Engineering—Legacy Subsurface Data Quality and Integration
2.17 Other

3.1 Well Planning and Execution—Deep, ERD, and Complex Well Design
3.2 Well Planning and Execution—Drilling in Overpressured and Unstable Formations
3.3 Well Planning and Execution—Performance Optimisation and Real-Time Decision Support
3.4 HPHT, Sour and Ultra-Deep Wells—HPHT and Sour Well Design and Execution
3.5 HPHT, Sour and Ultra-Deep Wells—Ultra-Sour Well Materials Selection and Integrity Management
3.6 HPHT, Sour and Ultra-Deep Wells—Sulphur Deposition Risk and Mitigation
3.7 HPHT, Sour and Ultra-Deep Wells—High-Consequence Risk Mitigation
3.8 Drilling Technologies and Automation—MPD, Advanced Fluids, and Lost-Circulation Solutions
3.9 Drilling Technologies and Automation—Automation, Remote Drilling, and Tool Integration
3.10 Well Integrity and Wellbore Fundamentals—Barrier Design and Verification
3.11 Well Integrity and Wellbore Fundamentals—Borehole Stability and Drilling Geomechanics
3.12 Well Integrity and Wellbore Fundamentals—Casing Design, Wear, and Sustained Casing Pressure
3.13 Digital, Data and AI Applications in Drilling—Data-Driven Drilling Optimisation and Performance Analytics
3.14 Digital, Data and AI Applications in Drilling—Automated Dysfunction Detection and Operational Risk Assessment
3.15 Other

4.1 Completions Design and Execution—Completion Strategies for Complex Reservoirs
4.2 Completions Design and Execution—Sand Control, Zonal Isolation, and Completion Integrity
4.3 Completions Design and Execution—Optimisation in Mature Fields
4.4 Stimulation and Reservoir Contact—Acidising and Hydraulic Fracturing
4.5 Stimulation and Reservoir Contact—Diagnostics, Placement Effectiveness, and Re-Stimulation
4.6 Well Intervention and Abandonment—Coiled Tubing and Light Intervention
4.7 Well Intervention and Abandonment—Integrity Remediation and P&A Best Practices
4.8 Well Intervention and Abandonment—Temporary Abandonment and Well Reuse
4.9 Digital, Data, and AI Applications in Completions and Intervention—Data-driven Design and Diagnostics
4.10 Digital, Data, and AI Applications in Completions and Intervention—Real-Time Monitoring and Reliability Analytics
4.11 Other

5.1 Production Optimisation—Artificial Lift and Late-Life Production
5.2 Production Optimisation—Flow Assurance and Production Chemistry
5.3 Well and Asset Integrity—Integrity Management and Life Extension
5.4 Well and Asset Integrity—Corrosion, Erosion, and Inspection Strategies
5.5 Well Testing, Logging, and Surveillance—Well Testing, PLT, and Rate-transient Analysis
5.6 Well Testing, Logging, and Surveillance—Surveillance of Complex and Commingled Wells
5.7 Energy Optimisation in Operations—Fuel Gas Reduction and Waste-Heat Recovery
5.8 Energy Optimisation in Operations—Hybrid Power and Heat Solutions
5.9 Digital, Data and AI Applications in Production—AI-based Production Optimisation and Predictive Maintenance
5.10 Digital, Data and AI Applications in Production—Digital Workflows for Remote and Exception-Based Operations
5.11 Other

6.1 Gas Field Development—Appraisal and Development De-risking for Gas/Condensate
6.2 Gas Field Development—Seal, Containment, and Leakage Risk
6.3 Gas Field Development—Gas Quality Screening (CO₂/H₂S/N₂)
6.4 Gas Field Development—Infrastructure-Constrained Development and Commerciality
6.5 Gas Processing and Treatment—Sour and Ultra-Sour Gas Processing at Commercial Scale
6.6 Gas Processing and Treatment—Sulphur Management: Forming, Storage, Logistics, and Compliance
6.7 Gas Processing and Treatment—Dehydration, Sweetening, and Sales-Gas Conditioning
6.8 Gas Processing and Treatment—Energy Efficiency and Plant Reliability
6.9 Gas Monetisation and Gas-to-Value—Monetisation Strategies Linked to Upstream Development
6.10 Gas Monetisation and Gas-to-Value—Gas-to-Chemicals and Polymer Feedstock Interfaces
6.11 Gas Monetisation and Gas-to-Value—LNG/CNG, Storage, and Midstream Options
6.12 Digital, Data, and AI Applications in Gas Operations—Data-driven Phase, Composition, and Deliverability Prediction
6.13 Digital, Data, and AI Applications in Gas Operations—Digital Decision Support for Appraisal and Concept Selection
6.14 Other

7.1 Facilities Design and Brownfield Optimisation—Onshore/Offshore Facilities and Debottlenecking
7.2 Facilities Design and Brownfield Optimisation—Tie-Ins, Revamps, and Subsea Tiebacks
7.3 Asset Reliability and Integrity—Rotating/Static Equipment Reliability
7.4 Asset Reliability and Integrity—Corrosion Management and Risk-Based Maintenance
7.5 Commissioning and Operations Readiness—Commissioning, Start-up, and SIMOPS
7.6 Commissioning and Operations Readiness—Handover and Readiness for Complex Assets
7.7 Pipelines, Flow Assurance, Marine, and Export Logistics—Pipeline Integrity and Export Flow Assurance
7.8 Pipelines, Flow Assurance, Marine, and Export Logistics—Hydrates, Wax, Corrosion, and Logistics
7.9 Pipelines, Flow Assurance, Marine, and Export Logistics—Marine Operations Under Seasonal, Environmental, and Access Constraints
7.10 Pipelines, Flow Assurance, Marine, and Export Logistics—Multi-Product Export Systems
7.11 Metering, Allocation, and Measurement—Fiscal/Non-Fiscal Metering and Uncertainty
7.12 Metering, Allocation, and Measurement—Allocation, Reconciliation, and Audit Readiness
7.13 Process Safety and Operational Risk—Process Safety Management and Barrier Health
7.14 Process Safety and Operational Risk—HAZID/HAZOP, Human Factors, and Major Accident Risk
7.15 Digital, Data, and AI Applications in Facilities and Midstream—Digital Twins and Predictive Maintenance
7.16 Digital, Data, and AI Applications in Facilities and Midstream—Smart Pipelines and Advanced Flow Assurance Analytics
7.17 Other

8.1 Improved Oil Recovery (IOR)—Waterflood Optimisation and Conformance Control
8.2 Improved Oil Recovery (IOR)—Pattern Management in Mature Fields
8.3 Improved Oil Recovery (IOR)—Surveillance-Driven IOR Decision-Making
8.4 Improved Oil Recovery (IOR)—Produced Water Handling and Mobility Control
8.5 Improved Oil Recovery (IOR)—Incremental Recovery from Brownfields and Late-Life Assets
8.6 Enhanced Oil Recovery (EOR)—Gas Injection (CO₂, N₂, Hydrocarbon Gas)
8.7 Enhanced Oil Recovery (EOR)—Chemical EOR (Polymer, Surfactant, ASP)
8.8 Enhanced Oil Recovery (EOR)—Low-Salinity and Hybrid EOR Processes
8.9 Enhanced Oil Recovery (EOR)—Thermal and Niche Thermal Applications
8.10 Enhanced Oil Recovery (EOR)—EOR Screening, Pilot Design, Economics, and Scale-up
8.11 Enhanced Oil Recovery (EOR)—Integration of EOR with CCUS and Emissions Reduction
8.12 Digital, Data and AI Applications in IOR/EOR—Data-Driven Candidate Screening
8.13 Digital, Data and AI Applications in IOR/EOR—Performance Surveillance and Conformance Analytics
8.14 Digital, Data and AI Applications in IOR/EOR—History Matching and Uncertainty Reduction for EOR Projects
8.15 Other

9.1 Resource Evaluation and Characterisation—Tight, Shale, Deep, and HPHT Reservoirs
9.2 Resource Evaluation and Characterisation—Petrophysics and Geomechanics
9.3 Drilling, Completion, and Stimulation—Multistage Fracturing and Operational Efficiency
9.4 Drilling, Completion, and Stimulation—Water Management and Well Interference
9.5 Development Planning and Scale-Up—Pilot-to-Development Pathways
9.6 Development Planning and Scale-Up—Supply Chain, Contracting, and Market Access
9.7 Digital, Data and AI Applications in Unconventionals—AI-Assisted Geosteering and Stimulation Diagnostics
9.8 Other

10.1 Emissions Reduction and Efficiency—Flaring, Methane, Electrification, and Energy Efficiency
10.2 CCUS and Subsurface Storage—CO₂ Storage, EOR Linkage, and Containment Assurance
10.3 Water, Waste and By-Product Management—Produced Water and Waste Management
10.4 Water, Waste and By-Product Management—Management of Solid By-Products (e.g., Sulphur)
10.5 Water, Waste and By-Product Management—Circularity and Valorisation Approaches
10.6 Geothermal and Subsurface Energy Reuse—Heat Recovery from Produced Fluids and Late-Life Assets
10.7 Digital, Data and AI Applications in Sustainability—Digital Emissions Monitoring and Environmental Analytics
10.8 End-of-Life and Decommissioning—Late-Life Strategies and Facilities Removal
10.9 Other

11.1 Overarching Digital Systems—Data Architecture, Governance, and Standards
11.2 Overarching Digital Systems—Integrated Asset Models and Digital Twins
11.3 Overarching Digital Systems—AI Deployment at Scale (Governance, MLOps)
11.4 Overarching Digital Systems—Cybersecurity and Digital Risk
11.5 Overarching Digital Systems—Adoption, Change, Capability Building, and People Development
11.6 Other

12.1 Integrated Development and Systems Optimisation—Subsurface–surface Integration and Phasing
12.2 Integrated Development and Systems Optimisation—Phased Development of Large Fields and Shared Infrastructure
12.3 Integrated Development and Systems Optimisation—Reservoir–Facilities–Market Integration
12.4 Project Management, Delivery, Cost, and Schedule—Cost Control, Productivity, and Execution Learnings
12.5 Case Studies and Lessons Learned—Transferable Case Studies and Decision Frameworks
12.6 Case Studies and Lessons Learned—Technology Deployment and Cross-regional Lessons
12.7 Local Content, Capability, and Workforce Development—Capability Development As a Project Delivery Enabler
12.8 Local Content, Capability, and Workforce Development—Skills Transfer, Localisation, and Technology Adoption
12.9 Other —Skills Transfer, Localisation, and Technology Adoption

Please note that abstract submissions should be formatted into four (4) specific paragraphs:

1. Objectives/Scope: Please list the objectives and/or scope of the proposed paper. (25–75 words)
2. Methods, Procedures, Process: Briefly explain your overall approach, including your methods, procedures and process. (75–100 words)
3. Results, Observations, Conclusions: Please describe the results, observations and conclusions of the proposed paper. (100–200 words)
4. Novel/Additive Information: Please explain how this paper will present novel (new) or additive information to the existing body of literature that can be of benefit to and/or add to the state of knowledge in the petroleum industry. (25–75 words)

 

The following guidelines apply

• DO NOT include title or author information in your abstract
• Word Minimum: 225
• Word Maximum: 450

SPE has adopted ORCID (Open Researcher and Contributor ID), a widely accepted unique identifier for authors, giving them control over their content and eliminating ambiguities. All SPE contributors are encouraged (but not required) to have an ORCID iD.  If you have an ORCiD, ID please add it to your SPE Member/Customer Profile. Login to SPE.org and update your profile today!

• Obtain the necessary clearance from your management, your partners, and customers BEFORE submission
• Authors whose paper proposals are accepted will be required to provide a manuscript for inclusion in the conference proceedings.
• Authors who do not submit a manuscript and the associated publication forms by the manuscript due date will be withdrawn from the program and will not be allowed to present per SPE’s No Paper, No Podium policy
• If accepted, your paper proposal may be published, as submitted, in conference information media, including on the SPE website.
• Authors will be notified on the status of their submissions by 31 July 2026 once the technical programme is finalised by the programme committee.
• An agreement to present a paper at this SPE conference carries an obligation to participate in the event. Please review SPE's Author Guidelines for Papers.

SPE has a stated policy against use of commercial trade names, company logos, or text that is commercial in tone in the paper title, text, or presentation slides. Use of such terms will result in careful scrutiny by the Program Committee in the evaluation of paper proposals, and the presence of commercialism in the paper will result in it being withdrawn from the program.

In an effort to further improve SPE’s technical quality standards, all submitted papers will be checked for plagiarism.

It is the responsibility of the author to obtain company clearance, to ensure the company understands that if the proposal is accepted, you will be required to travel to the event to present. All travel expenses (airfare, hotel, registration) associated with attending the conference are the responsibility of company or individual attending.

If you are interested in writing a paper, SPE has a variety of resources to help you contribute to the knowledge and future of the upstream oil and gas industry.

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