On-demand seismic processing on AWS using GeoTomo’s technology

The seismic methods are the most common and effective ways for subsurface imaging to delineate and characterize oil and gas reservoirs. Seismic data are acquired in the field by deploying a seismic source (vibrator) that radiates elastic waves into the subsurface. The waves travel through the formations and are reflected back due to the variation in the elastic properties of the geological layers. The reflected, refracted, and diffracted seismic waves and the accompanying various types of noise that contaminate the seismic signal are then recorded by the receivers – geophones on land and hydrophones in marine seismic surveys. By seismic processing, raw data are transformed to a subsurface image using a workflow comprised of several steps that are I/O intensive and computationally intensive. The seismic image obtained from seismic processing along with other subsurface related data such as well logs are used for making multimillion-dollar business decisions in the oil and gas industry.

Seismic data processing comprises three principal stages: signal processing of recorded data, velocity estimation, and seismic imaging. Land seismic data processing includes the additional stage of near-surface modeling for statics corrections. Signal processing is aimed at enhancing reflections and suppressing coherent and random noise in the recorded data, and includes a number of steps for single-channel processing and multichannel processing with residual statics corrections interleaved between the single and multichannel processing steps. Estimation of stacking velocities, rms velocities, and interval velocities are I/O intensive and computationally intensive, especially for 3D seismic data. These velocities are used for stacking, time and depth migrations, respectively. Seismic imaging is performed both in time and in depth by way of prestack time and depth migration algorithms, which, again, are I/O intensive and computationally intensive.

Seismic processing jobs, are executed by specialist seismic processor companies using on-premises high-performance computing (HPC) centers that require extensive IT infrastructure planning to setup with major capital investments upfront. There is a push in the industry to move to higher resolution and denser seismic surveys, where closer survey spacings result in much greater amounts of raw data for processing, and we can expect orders of magnitude increase over the coming years. Cloud technologies can relieve most of the pain points related to HPC as discussed in this article. In a report on the state of computational engineering, 78% of engineers are using cloud-based HPC with over 50% using it consistently for engineering and science workloads.

Problem definition and industry challenges

Each step or job executed in the seismic processing workflow involves gigabyte to terabyte scale of data. The total process to go from the raw data to the seismic image could take from weeks to months to complete depending on the size of the acquisition and the workflow applied. Different vintages of seismic processing products are obtained by applying different algorithms or variations of the seismic processing workflow.

Many major exploration and production (E&P) companies are using on-premises HPC centers for executing seismic processing workflows. Contracts are also awarded by the E&P companies to specialized seismic processing service providers for turn-key seismic data processing services. Executing seismic processing jobs in an HPC environment requires detailed business and IT infrastructure resources planning. The IT infrastructure for I/O and computational requirements – increases exponentially as we collect more seismic data in the field and use more advanced algorithms to get better seismic images from the collected data. HPC evolution in the oil and gas industry shows the exponential increase in compute requirements with advancements in the seismic imaging. This heavy resource overhead inhibits the ability to experiment and innovate by executing processing workflows based on immediate business needs. As a result, many of our customers have expressed interest to have an on-demand seismic processing solution.

The On-demand seismic processing (OdSP) solution

An OdSP is a seismic processing HPC solution in the cloud. The OdSP solution in the AWS Cloud executes seismic processing jobs in a cost-managed, fully scalable, and turn-key delivered HPC environment. A HPC cluster for OdSP can be created in the cloud at any time, scaled as needed, and dissolved when the project is complete. There’s no limit of how many HPC clusters can be created as needed to run multiple seismic processing jobs. Such approach will eliminate a need to wait in queue for a completion of another job.

Figure: OdSP on AWS using GeoTomo’s technology reference architecture

The OdSP solution on AWS starts with uploading the data from data centers to the AWS cloud into Amazon S3 buckets. A wide variety of cloud data migration tools from AWS can be used for this purpose. AWS Parallel Cluster helps in the automatic orchestration of the cluster resources on AWS. The cluster definition is done using a configuration file that contains the details of the cluster, for example: the type of instances for head node and compute nodes, the number of compute nodes and others. Session Manager from AWS Systems manager can be used for launching the cluster. Alternately, a cloud IDE such as AWS Cloud9 can also be used for the same process. AWS parallel cluster has options to manage HPC jobs using REST API. AWS Parallel Cluster makes a custom Cluster CloudWatch dashboard to monitor the cluster performance. This dashboard can be customized to include metrics of interest such as memory consumption. The seismic processing software is installed in a separate instance referred as the seismic processing software node. This includes GeoTomo software that users use to submit seismic processing jobs on-demand to the cluster and visualize the results obtained from the execution of the jobs. In this case, a g4dn instance is used for the seismic processing software node. Nice DCV visualization client provides virtual desktop streaming capability for remote visualization. Amazon FSx for Lustre high performance storage system provides high performance I/O capabilities for this solution. AWS Parallel Cluster mounts storage automatically to the compute node when the job starts. The storage system is synchronized with Amazon S3 bucket for retaining results of running the seismic processing jobs in Amazon S3 bucket when the rest of the resources are released after the job is completed.

OdSP using GeoTomo’s technology

The seismic processing software in the OdSP solution on AWS uses GeoTomo’s software – TomoPlus and GeoThrust. TomoPlus is a comprehensive near-surface solutions package with multiple algorithms designed to obtain accurate near-surface velocity models and derive long and short-wavelength statics solutions for land, ocean bottom nodes and shallow marine seismic data. GeoThrust is an advanced 2D/3D Seismic Data Processing system that goes from raw field data through to Prestack Time Migration and Prestack Depth Migration. The OdSP solution using GeoTomo’s technology gives an end-to-end seismic processing workflow – from execution to visualization and analysis of results. The solution enables customers to run multiple scenarios simultaneously and narrow uncertainty in the results. The solution also provides flexible configuration options to quickly iterate resource selection and ensure cost optimization.

Figure: 3D seismic volume visualized using GeoTomo’s software

Conclusion

The OdSP solution eliminates the need for elaborate IT planning and prioritization of seismic processing jobs. This brings agility to the business by providing results faster which leads to E&P companies significantly reducing their exploration cycle. Cost reduction is achieved when virtual seismic data centers can be instantiated as needed in the cloud and follow customers demand cycle. Ideal price/performance ratio guarantees low cost for each individual run making the whole processing job cost effective. Contact us today to find out how we can help optimize your downstream business outcomes.