On-premise HPC centres for seismic processing demand $2M to $5M in initial hardware procurement, $800K to $1.2M in annual facility costs for power, cooling, and floor space, and a forced hardware refresh cycle every 3 to 5 years that disrupts processing schedules and ties up capital that could fund exploration. During low-demand periods between survey campaigns, 40 to 50 percent of that compute capacity sits idle while still consuming power and generating maintenance costs. iFactory cloud seismic processing eliminates this entire cost structure by migrating your processing and interpretation workloads to elastic GPU clusters that scale from 32 cores to over 1,000 GPUs on demand, with zero upfront capital and per-minute billing that aligns compute cost directly with actual processing workload. Book a Demo to see your seismic workflows running on cloud GPU clusters with benchmarked performance results.
10x
GPU acceleration factor for seismic migration vs CPU on-prem clusters
$4.2M
Average annual infrastructure cost eliminated by cloud migration per processing centre
0
Hardware refresh cycles required with cloud GPU access to latest architectures
15 min
Time to provision a 512-GPU cluster from zero to processing-ready state
Every Idle GPU Minute on Premise Is Wasted Capital. Cloud Elastic Scaling Pays Only When You Process.
iFactory migrates your seismic processing, migration, inversion, and interpretation workflows to cloud GPU infrastructure — delivering 10x speedup, eliminating hardware refresh cycles, and reducing total processing cost by 60 to 85 percent for standard survey workloads.
The On-Premise HPC Cost Trap vs Cloud GPU Economics
Before evaluating cloud migration, understand the full cost structure that on-premise HPC centres impose on seismic processing operations — capital that could directly fund additional seismic acquisition, well programmes, or basin analysis instead of sitting in server racks.
On-Premise HPC
$2M–$5M initial hardware for CPU/GPU clusters, storage arrays, and networking infrastructure with 6 to 12 month procurement lead times
$800K–$1.2M annual facility costs for data centre floor space, power consumption, cooling systems, and physical security
3 to 5 year forced refresh cycle requiring capital budget approval, procurement, migration, and 4 to 8 weeks of processing downtime
40 to 50 percent idle capacity between survey campaigns while still consuming power, generating heat, and requiring maintenance
Dedicated IT staff for system administration, security patching, storage management, and hardware troubleshooting
Cloud GPU Processing
Zero upfront hardware cost with per-minute or per-GPU-hour billing that converts capital expenditure to operational expenditure
No facility overhead — power, cooling, floor space, and physical security fully included in compute pricing
Instant architecture upgrades — access to NVIDIA A100, H100, and next-generation GPUs without procurement or migration
Scale to zero when idle — no compute charges when processing is complete, eliminating idle capacity waste entirely
Managed infrastructure with 99.9% availability SLA, automated patching, and elastic storage that grows with your data
Cloud Processing Architecture: From Data Upload to Interpretation-Ready Output
iFactory's cloud seismic processing platform follows a six-stage pipeline that ingests your raw field data, executes GPU-accelerated processing workflows, and delivers interpretation-ready volumes to your desktop — all within a fully managed, encrypted cloud environment. Talk to our cloud migration team about adapting this pipeline to your specific processing workflows.
01
Seismic Data Ingestion
Raw SEG-Y, SEG-D, and field tape data uploaded to encrypted cloud object storage via high-bandwidth transfer with automatic format validation and quality control metadata generation.
02
GPU Cluster Provisioning
Processing workflow analysed for compute requirements. Optimal GPU instance type and count selected automatically. Cluster provisioned and validated in under 15 minutes with interconnect configuration.
03
Parallel Processing Execution
Seismic processing workflows — deconvolution, NMO, stack, migration, inversion — distributed across GPU nodes with automatic load balancing, checkpoint recovery, and progress monitoring.
04
Quality Control Validation
Automated QC checks on processed outputs including amplitude fidelity, frequency content, signal-to-noise ratio, and spatial consistency. Anomalies flagged for interpreter review before final delivery.
05
Cloud Interpretation Access
Processed volumes mounted directly to cloud-based interpretation workstations with full visualisation capability. Multiple interpreters access the same data simultaneously without local download.
06
Output Export and Archival
Final processed volumes exported in standard formats for local use. Source data and intermediate products archived in tiered cloud storage with automated lifecycle policies and retrieval capability.
Elastic GPU Scaling: Match Compute to Workload, Not the Other Way Around
On-premise HPC forces you to size hardware for peak demand and accept the cost of idle capacity during normal operations. Cloud GPU processing inverts this model — you provision exactly the compute you need, for exactly the duration you need it, scaling up and down as your processing workload demands.
Routine Processing
Reprocessing, quality control, small-area updates
32 GPUs
$180/hr
Standard 3D Survey
Full 3D processing, pre-stack migration, AVO
128 GPUs
$720/hr
Large Basin Survey
Basin-wide processing, broadband, multi-survey merge
512 GPUs
$2,880/hr
Peak RTM and FWI
Full wavefield inversion, reverse time migration, imaging
1,024 GPUs
$5,760/hr
Scale back to zero GPUs when processing completes. No idle charges. No hardware to maintain. Procure compute in minutes, not months.
GPU-Accelerated Processing Benchmarks: Cloud vs On-Premise Performance
The following benchmarks compare processing times for standard seismic workflows executed on on-premise CPU clusters versus iFactory's cloud GPU processing platform, measured on identical input datasets from active offshore survey programmes.
Pre-Stack Time Migration
On-Prem CPU
18 days
vs
Cloud GPU
1.8 days
10x Speedup
Reverse Time Migration
On-Prem CPU
45 days
vs
Cloud GPU
3.8 days
12x Speedup
Full Waveform Inversion
On-Prem CPU
90 days
vs
Cloud GPU
7.5 days
12x Speedup
3D SRME Multiple Attenuation
On-Prem CPU
12 days
vs
Cloud GPU
1.5 days
8x Speedup
Surface-Related Multiple Prediction
On-Prem CPU
8 days
vs
Cloud GPU
0.9 days
9x Speedup
Post-Stack Depth Migration
On-Prem CPU
5 days
vs
Cloud GPU
0.6 days
8x Speedup
Your On-Premise Cluster Is Processing at 10x the Cost Per GPU-Hour of Cloud Infrastructure. The Math Does Not Improve With Age.
iFactory migrates your seismic processing to cloud GPU clusters with zero upfront capital, 10x processing speedup, and elastic scaling that eliminates idle compute costs. Full migration completed in 12 weeks with continuous processing capability maintained throughout.
12-Week Cloud Migration Roadmap with Continuous Processing Capability
Every iFactory cloud migration follows a structured 12-week programme with defined deliverables per phase. Processing continues on-premise throughout the migration period, with no production downtime or workflow interruption during the transition.
Phase 1
Assessment and Planning
Weeks 1–3
Inventory all processing workflows, data volumes, and compute requirements
Map GPU requirements per workflow type and identify cloud-optimised alternatives
Define data security, encryption, and compliance requirements for cloud deployment
Phase 2
Data Migration and Environment Setup
Weeks 4–6
Transfer seismic data to encrypted cloud object storage with integrity verification
Provision cloud processing environment with GPU instances, networking, and storage tiers
Configure security groups, access controls, and data residency compliance
Phase 3
Workflow Porting and Benchmarking
Weeks 7–9
Adapt processing workflows to cloud GPU architecture with optimisation for parallel execution
Execute benchmark processing runs comparing cloud output against on-prem results
Validate amplitude fidelity, frequency content, and spatial accuracy of cloud-processed outputs
Phase 4
Production Cutover and Optimisation
Weeks 10–12
Transition primary processing workload to cloud platform with on-prem fallback capability
Train processing teams on cloud workflow management, cost monitoring, and scaling controls
Deliver cost benchmarking report comparing cloud vs on-prem TCO over 3-year projection
Cloud GPU Processing vs On-Premise HPC: Operational Comparison
The table below compares iFactory's cloud GPU processing platform against on-premise HPC infrastructure across the dimensions that determine processing capability, cost efficiency, and operational agility for seismic interpretation teams.
| Dimension | On-Premise HPC | iFactory Cloud GPU Platform |
|---|---|---|
| Compute Scaling | Fixed capacity sized for peak demand. Scaling requires hardware procurement with 6 to 12 month lead times and capital budget approval. | Elastic scaling from 32 to 1,024+ GPUs provisioned in under 15 minutes. Scale to zero when processing completes with no idle charges. |
| GPU Access | Limited to GPUs purchased at time of hardware refresh. Architecture becomes outdated within 2 to 3 years of deployment with no upgrade path without full replacement. | Instant access to latest NVIDIA A100, H100, and next-generation GPU architectures without procurement, migration, or capital expenditure. |
| Storage Capacity | Fixed storage capacity requiring advance capacity planning. Expansion requires additional hardware procurement and installation during scheduled maintenance windows. | Elastic object storage that grows with your data. Automatic tiering between hot, warm, and cold storage based on access frequency and cost optimisation. |
| Processing Speed | Limited by installed CPU/GPU count and interconnect bandwidth. Peak workloads queue behind other jobs with first-in-first-out scheduling delays. | Dedicated GPU clusters per processing job with no queue contention. 8 to 12x speedup for migration and inversion workloads on current-generation GPUs. |
| Cost Model | Capital expenditure for hardware plus fixed annual operating costs regardless of utilisation. Total cost remains constant whether processing 1 survey or 10 surveys per year. | Operational expenditure with per-GPU-hour billing. Total cost scales directly with processing workload — zero cost when idle, proportional cost when active. |
| Data Security | Physical security within operator-controlled data centre. Requires dedicated security staff, firewalls, intrusion detection, and compliance audit management. | Encrypted data at rest and in transit with key management. Cloud provider security certifications including SOC 2, ISO 27001, and data residency controls. |
| Interpretation Access | Data must be transferred from processing cluster to interpretation workstations via local network. Remote access requires VPN with bandwidth limitations. | Processed volumes mounted directly to cloud interpretation workstations accessible from any location. Multiple interpreters collaborate on the same data simultaneously. |
Cloud Migration Outcomes: Processing Centres That Eliminated On-Premise HPC
The following outcomes reflect actual iFactory cloud migration projects across three operator types with distinct processing volumes, workflow complexity, and cost structures. Each migration was completed within the 12-week programme with continuous on-premise processing maintained throughout. Book a Demo to discuss migrating your processing centre to cloud GPU infrastructure.
Major Operator — Gulf of Mexico
RTM Processing Cloud Migration for Deepwater Exploration Programme
A major operator running an intensive deepwater RTM processing campaign migrated from a 512-CPU on-premise cluster to iFactory cloud GPU processing. The migration covered 6 surveys totalling 4,800 km2 with pre-stack RTM as the primary workflow. Cloud GPU processing delivered 12x speedup on RTM compared to the on-prem CPU cluster, reducing individual survey processing from 45 days to 3.8 days. The operator completed the entire 6-survey RTM campaign in 8 weeks on cloud versus the projected 9 months on-prem, accelerating exploration cycle time by 7 months. Annual infrastructure cost reduction of $4.8M included elimination of hardware refresh capital, facility costs, and dedicated HPC administration staff. The operator decommissioned the on-premise cluster entirely within 3 months of migration completion.
12x
RTM speedup on cloud GPU
7 months
Exploration cycle time saved
$4.8M
Annual infrastructure cost eliminated
Independent Producer — West Africa
Full 3D Processing Burst for 2,500 km2 Exploration Survey
An independent producer with no on-premise HPC infrastructure required full 3D processing of a newly acquired 2,500 km2 survey offshore West Africa. Rather than procuring a dedicated processing cluster for a one-time workload, the operator engaged iFactory to process the entire survey on cloud GPU infrastructure. The processing campaign including deconvolution, multiple attenuation, velocity analysis, pre-stack migration, and AVO analysis was completed in 6 weeks using an elastic cloud GPU allocation that scaled from 64 GPUs during initial processing to 512 GPUs during migration phases, then back to zero upon completion. Total cloud processing cost of $380,000 represented an 82% cost reduction compared to the estimated $2.1M for a comparable on-prem cluster build-out including hardware, facilities, and staff allocation for the same processing scope.
82%
Cost reduction vs on-prem build-out
6 weeks
Full 3D processing turnaround
$380K
Total cloud processing cost
National Oil Company — Southeast Asia
Legacy Survey Reprocessing Batch on Cloud GPU Infrastructure
A national oil company required reprocessing of 8 legacy 3D surveys totalling 6,200 km2 to apply modern broadband processing techniques and update regional interpretation. The on-premise processing centre had a 14-month queue for the reprocessing batch. iFactory cloud GPU processing completed the entire 8-survey batch in 10 weeks by provisioning 256 GPUs continuously during the campaign, with弹性scaling to 512 GPUs during the migration phases of each survey. The 10-week cloud campaign eliminated the 14-month queue delay, enabling the interpretation team to begin regional reassessment 11 months ahead of the on-prem schedule. The operator retained the on-premise cluster for routine processing but established cloud GPU as the standard platform for all burst and batch processing workloads going forward.
11 months
Queue delay eliminated by cloud batch
10 weeks
8-survey reprocessing campaign duration
6,200 km2
Total legacy survey area reprocessed
Frequently Asked Questions
How does iFactory ensure data security and compliance when seismic data is stored and processed in the cloud?
iFactory implements AES-256 encryption for all data at rest and TLS 1.3 encryption for all data in transit, with customer-managed encryption keys that ensure only your organisation can decrypt your seismic data. Cloud infrastructure is deployed within specific geographic regions to meet data residency requirements applicable to your operating jurisdictions. The platform operates within cloud provider environments that maintain SOC 2 Type II, ISO 27001, and CS STAR certifications. Access controls follow role-based permissions with multi-factor authentication, and all data access is logged for audit trail purposes. For operators with additional security requirements, dedicated tenancy and virtual private cloud configurations are available. Contact our support team to discuss your specific security and compliance requirements.
Can existing seismic processing workflows from vendors like CGG, Schlumberger, or Paradigm run on iFactory cloud GPU infrastructure?
Yes, iFactory's cloud environment supports commercial seismic processing software from all major vendors including CGG GeoCluster, Schlumberger Omega, and Emerson Paradise. During the Phase 3 benchmarking period, your existing workflows are ported to the cloud environment with GPU optimisation applied where possible. For workflows that cannot be GPU-accelerated, CPU instances are provisioned alongside GPU instances within the same cluster to ensure complete workflow compatibility. The platform also supports open-source processing frameworks including Seismic Unix and Madagascar for operators who maintain custom processing flows. Book a demo to see your specific vendor workflows running on cloud GPU infrastructure.
What is the actual cost per GPU-hour and how does it compare to the effective cost of on-premise compute?
Cloud GPU pricing varies by instance type and region, but effective rates for NVIDIA A100 GPUs typically range from $2.50 to $4.00 per GPU-hour including all infrastructure costs. When compared to on-premise effective cost — which includes hardware depreciation, facility power and cooling, floor space, IT staff allocation, and maintenance contracts — the cloud GPU rate is typically 60 to 85 percent lower per compute unit because on-premise costs include the burden of idle capacity that cloud eliminates entirely. During the Phase 4 cutover, iFactory delivers a detailed TCO comparison showing your specific on-prem effective cost per GPU-hour versus projected cloud cost based on your actual processing workload patterns. Reach out to support to request a TCO analysis for your processing centre.
How does cloud data transfer performance compare to local storage access for large 3D seismic volumes?
Cloud object storage delivers sustained read throughput of 10 to 25 GB per second for seismic data access patterns, which matches or exceeds the performance of many on-premise NAS and SAN systems that processing teams currently use. For processing workflows with high I/O requirements, iFactory provisions high-throughput file systems with GPUDirect Storage capability that allows GPUs to read data directly from cloud storage without CPU intermediary, further reducing I/O latency. During data migration in Phase 2, dedicated high-bandwidth transfer channels achieve ingestion rates of 5 to 15 GB per second for initial bulk data transfer, with subsequent incremental transfers occurring at similar rates. Book a demo to review storage performance benchmarks for your data volume requirements.
What happens if our organisation decides to repatriate data from the cloud back to on-premise storage in the future?
iFactory ensures complete data portability throughout the cloud deployment. All processed outputs, intermediate products, and source data remain in standard industry formats including SEG-Y, SEG-D, and standard grid formats that can be downloaded and transferred to any on-premise storage system at any time. Data egress capabilities support high-bandwidth transfer for bulk repatriation, and iFactory provides data export tooling that packages datasets with metadata and processing history for seamless re-import into on-premise environments. There are no proprietary lock-in formats or platform-specific data structures that would prevent complete data retrieval. The cloud environment is designed as a processing and interpretation platform, not a data custody solution, giving your organisation full control over data location at all times. Connect with support to discuss data portability and repatriation procedures.
Stop Paying for Idle GPUs, Outdated Hardware, and Data Centre Overhead. Migrate to Cloud Seismic Processing in 12 Weeks with Zero Downtime.
iFactory delivers 10x GPU processing speedup, elastic scaling from 32 to 1,024 GPUs, zero upfront capital, and full data security with encrypted cloud infrastructure — with your existing workflows, your existing software, and your existing team.
