SGBF Presentation Schedule

Presentation Schedule

Fast Stochastic Inversion: An Improved Seismic Inversion Method That Accelerates Time to Results

Session Theme: Velocity Modeling & Uncertainties October 19, 14:00 | Room: Barra

A Next-Generation Seismic Processing and Imaging Platform

Join us on the exhibit floor!

Tuesday 11:45 AM | Wednesday 2:15 PM | Thursday 11:00 AM

Booth #13

Click here for more info AspenTech at SGBF

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Tuesday 4:30 PM | Wednesday 11:45 AM | Thursday 2:15 PM

Seamless Integration of Structural Uncertainties and Reservoir Properties - A Workflow for Automatic Model Updates

Constrained Velocity Modeling and Updating for a Pre-salt Environment

Gas Prospect De-risking in the Drava Basin: An Unbiased Approach Using Neural Networks (A joint case study with INA)

Tuesday 1:30 PM | Wednesday 4:30 PM

Tuesday 9:30 AM | Wednesday 3:00 PM | Thursday 10:15 AM

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Tuesday 2:15 PM | Wednesday 1:30 PM | Thursday 1:30 PM

Advanced Seismic Interpretation Using Multi-Azimuth Analysis

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Tuesday 3:45 PM | Wednesday 11:00 AM | Thursday 9:30 AM

Rock Type Classification and Flow Unit Identification: Understanding Porosity-Permeability Relationships

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Tuesday 10:15 AM | Wednesday 3:45 PM | Thursday 11:45 AM

Seamless Integration of Structural Uncertainties and Reservoir Properties: A Workflow for Automatic Model Updates

Stochastic inversion is a well-known geostatistical technique for inverting seismic data into rock properties while incorporating uncertainty estimation and high-resolution results. It is used to explore geological features that are beyond the resolution of seismic data. Analysis of the results enables the evaluation of uncertainties about the potential presence of various geological features, their location, thickness, connectivity, etc. However, classic stochastic inversion is a very expensive process in terms of computational time; consequently, only a few realizations are usually generated. This may negatively impact risk assessment. The goal of this presentation is not to discuss the benefits of running a stochastic inversion; rather, we will note some general drawbacks of the geostatistical inversion method when attempting to accurately estimate subsurface rock properties. We will then show how a new approach (Fast Stochastic Inversion) is able to increase the number of realizations, without compromising results.

Presented by João Muniz

AspenTech's Next-Generation Processing & Imaging system delivers a fresh user interface and brand-new project management utilities, to support and enhance the geophysical workflows upon which our customers rely. This new system validates and extends the geophysical reputation of AspenTech SSE, bringing our depth of technology into a future-proofed system, fit-for-purpose in today’s demanding software environment and optimized for advances in hardware technology. Together, they deliver best-in-class efficiency. This presentation will detail the key components of this development, including a demonstration of the new applications.

Presented by Caio Barros/Jaime Yañez

Aspen RMS reservoir modeling software is a geoscience and reservoir engineering solution for creating and optimizing 3D reservoir models and increasing understanding of the reservoir. RMS provides unique flexibility to operators integrating multiple data types, capturing and propagating uncertainties across their workflows, and preserving data and geologic integrity, from seismic to production. In this session, we will learn how to construct a robust structural uncertainty model. This comprehensive solution combines interpreted seismic data, velocities, geologic trends, well data and their associated uncertainties to produce an optimal structural model or an ensemble of coherent models that represent how uncertainty varies spatially. Operators can effortlessly incorporate these structural uncertainties into Aspen Big Loop ensemble automation workflows for history matching and production forecasting. Asset teams can quantify the impact of the horizon and fault uncertainty on production, as well as the risks associated with field development and reservoir management decisions.

Presented by Horacio Vera

Featured Technologies: Aspen SeisEarth™ QSI

Featured Technology: Aspen NextGen P&I

Featured technology: Aspen RMS™, Aspen Big Loop™

Featured technology: Aspen SKUA™/Aspen GeoDepth™

Improved imaging of pre-salt structures and reservoirs is strongly influenced by the quality of the velocity models used in the seismic processing. These velocity models need to consider different geological characteristics, such as the presence of a thick and heterogeneous salt layer, and the different formations of the post-salt section with back-turtle structures, mass flow deposits, igneous intrusions, and others. A constrained model, in addition to allowing more accurate images, also provides more reliable input for QI workflows or geomechanical modeling. It is relevant to updating velocity models in a quick and precise manner in order to incorporate new information from drilled wells. In this presentation, solutions are suggested for the different challenges involved in creating and updating velocity models consistent with the geological scenario.

Presented by Maria González

Featured technology: Aspen SeisEarth™

Whether aspiring to optimize O&G exploration and production, or seeking appropriate carbon storage sites, energy companies must be efficient and productive when working with seismic data. They require a seismic interpretation system that can handle diverse data types and offer a rich set of interpretation and characterization methods that are adaptable to multiple exploration and development objectives. AspenTech offers best-in-class interpretation tools in its Integrated Canvas. There, geoscientists can easily perform workflow-guided interpretation tasks, generate interval attributes, apply machine learning methods, and apply modern voxel visualization and detection techniques. All of these methods can be used with prestack seismic data and advanced Quantitative Interpretation methods so that direct hydrocarbon indicators can be incorporated into the interpretation workflow. These easily accessible capabilities allow geoscientists to quickly sift through their data and confidently identify and rank opportunities for their company’s long-term strategy, in tune with today’s global challenges.

Presented by Raisa Carvalho

Featured technology: Aspen EarthStudy 360™/QSI

Although diffracted energy is recorded during data acquisition, it is suppressed by conventional processing and standard imaging algorithms, where summations and averaging processes are applied. This results in the loss of high-resolution structural information. This presentation includes several case studies that show the generation of high-resolution subsurface images containing various types and scales of discontinuous geometrical objects. We will also discuss different workflows for leveraging the traditional seismic interpretation workflow by integrating information relative to diffraction energy, like any other poststack attribute to be interpreted. The presentation also shows techniques for handling multi-azimuth data, and for performing analyses to extract and use information about amplitude (AVAZ) and velocity (VVAZ) variation in respect to that data. Azimuthal variations are caused by fractures or azimuthal stress variations, and we can learn from traveltime variations about the nature of the fractures.

Presented by Vinicius Ramos

Resolving deep subsalt reflectivity is a challenge for conventional FWI and imaging methods. These challenges are imposed by complex wave pathing in the presence of salt, interference from surface and interbed multiples, salt velocity variations and limitations in current FWI methods to properly recover both the kinematic and dynamic characteristics of the recorded wavefield. This presentation will apply targeted objectives functions embedded in different FWI inversion schemes, including adaptive waveform inversion, constrained waveform inversion, reflection waveform inversion and least squares FWI. When combined, these inversion schemes (and corresponding objective functions), not only automate and compress the timeline in the velocity model-building process, but also provide the pathway to the recovery of interpretable reflectivities.

Presented by: Nikhil Shah, CEO S-Cube

Featured Technologies: S-Cube (XWI suite), Aspen Technology Seismic Imaging and Velocity Modeling Solutions

Featured technology: Aspen GeoDepth™ Refraction-Reflection Tomography

One of the main challenges in seismic imaging, especially of land data, is building the near surface velocity model, as it is normally characterized by very low velocity values with different types of local anomalies. Resolving the near surface velocity model using only refraction data (e.g., refraction tomography) is insufficient, as it does not provide the required lateral resolution. Using only reflection data is equally insufficient, as it does not provide the required vertical resolution. We present a tomographic approach for simultaneously resolving the shallow and deep subsurface anisotropic velocity fields, where we jointly utilize both reflection and refraction data. By constructing a constrained joint reflection-refraction objective function, this tomography can provide high-resolution anisotropic velocity models and subsequent accurate depth migration images. We apply the method to a 3D dataset from the Eagle Ford play. The results demonstrate that the method produces very accurate anisotropic velocity models, at shallow and deep levels.

Presented by: Gabriel Perez

Featured technology: Aspen EarthStudy 360™

Full-azimuth wavefield decomposition Local Angle Domain (LAD) imaging uses the complete recorded wavefield to provide a highly accurate and detailed description of the subsurface. The initial outputs of LAD imaging are reflectivity angle azimuth gathers and directivity angle azimuth gathers. These organize the recorded seismic data into novel formats to optimize the use of azimuthal data and allow the creation of alternative images suitable for high-resolution prospecting. Operations performed on the full-azimuth directivity gathers generate preferential images that emphasize reflection continuity (specular) or reflection discontinuity (diffraction), providing seismic processing and interpretation professionals with a better understanding of reservoir compartmentalization and depositional history, and enabling them to target specific geologic features. Alternatively, model-based Q filters can be incorporated into LAD ray tracing to compensate for energy absorption while correcting wavelet distortions caused by subsurface attenuation. This presentation will include examples of all these seismic images applied to both onshore and offshoreseismic data. The benefits of rich azimuth acquisitions will be reinforced through these examples.

Presented by: Bruno de Ribet

Featured technology: Aspen SeisEarth™ QSI Stochastic Inversion

Presented by: Dennis Ellison

Featured technology: Aspen SeisEarth™ Lithology Prediction

In a mature onshore field, a prospect has been identified based on amplitude anomalies detection and targeting gas sand reservoirs associated with basin floor turbidites. This prospect has analogs in nearby fields where anomalies were previously drilled. While some were commercial saturated gas sands, others were related to low-saturated gas sands or low-velocity shales. Amplitude versus offset (AVO) and spectral decomposition are known techniques for successful direct hydrocarbon identification and contribute significantly to differentiating between different fluid types and lithologies. Such methods for prospect quality analysis are tedious, however, and final interpretation results rely on subjective and empirical analysis, without unbiased integration. We propose a Machine Learning approach, which eliminates the need for a separate analysis of the DHI attributes and achieves integration. To better quantify the risk associated with the prospect, both AVO and spectral decomposition were used in an unsupervised classification analysis. We will show how this classification method delivers an effective and unbiased assessment of the prospect.

Presented by: Bruno de Ribet

Featured technology: Aspen SeisEarth™ (with connectivity to Aspen SKUA™, Aspen P&I solutions, OSDU )

Presented by: Zahary Vera

• Selecting the best software for each stage of the workflow • Avoiding a reduction in productivity due to differences in user interfaces and applications • Project deadlines and budget constraints • Risks associated with loss of information when transferring data between systems

Whether involved in resource extraction or supporting the Energy Transition effort, a significant concern of geoscientists is the need to continuously move data between databases and application suites to complete workflows when working with separate packages. These challenges may include:

This presentation illustrates a full interpretation and characterization workflow performed in a single solution, Aspen SeisEarth. Direct connectivity and data sharing between Aspen SSE processing & imaging, formation evaluation, and reservoir modeling and engineering solutions, enabled by a unique and innovative shared licensing model, provide geoscientists with the ability to expand their workflows across the full gamut ofsubsurface evaluation and characterization processes. In this presentation, we will also show how SeisEarth connects directly to seismic and well DMSs in OSDU, providing a straightforward means of accessing data from third-party sources. As a contributing member of the Open Subsurface Data Universe (OSDU) platform community, AspenTech is fully committed to enabling our solutions to run directly against OSDU Data Management Services and take full advantage of the opportunities for cross-vendor interoperability provided by the platform.

Featured technology: Aspen Geolog™ Facimage

Reservoir characterization and formation evaluation play a pivotal role in maximizing hydrocarbon recovery. A critical piece of reservoir characterization is understanding the relationship between flow capacity andstorage capacity within an asset. Conventional methods characterize and quantify permeability (flow capacity) from porosity to obtain an expression based on discrete measurements (core data) to extrapolate using wireline logs. The drawback with this method assumes a single expression can model all reservoir rocks. However, multiple studies demonstrate that for the same porosity value, permeability can vary by several orders of magnitude. Such variability indicates the existence of different rock types that can be grouped into “flow units” defined by storage (porosity) and flow (permeability) capacity. To assess these flow units, geoscientists can determine a rock quality indicator that can aid in creating groups of rocks with the same quality or type. This indicator can allow users to apply a specific permeability expression to a specific rock type and provide a better, more accurate flow capacity estimate. In this session we will demonstrate how these methodologies for rock type characterization can be implemented easily in Aspen Geolog™, and leverage Machine Learning techniques to calculate an accurate permeability log.

Presented by: Kim McLean

Featured technology: Aspen Technology Geomodeling Solutions

3D reservoir models combined with supporting reservoir engineering solutions increase understanding of reservoir flow and performance. These solutions provide unique flexibility to operators integrating multipledata types, capturing and propagating uncertainties across their workflows, and preserving data and geologicintegrity from seismic to production. In this session, we will learn how to construct a robust structural uncertainty model. This comprehensive solution combines interpreted seismic data, velocities, geologic trends, well data and their associated uncertainties to produce an optimal structural model or an ensemble of coherent models that represent how uncertainty varies spatially. Operators can effortlessly incorporate these structural uncertainties into Aspen Big Loop™ ensemble automation workflows for history matching and production forecasting. Asset teams can quantify the impact of the horizon and fault uncertainty on production as well as the risks associated with field development and reservoir management decisions.

Presented by: Sasan Ghanbari

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Tuesday 15:30 Wednesday 15:30

Fast Seismic Interpretation Workshop

Featured technology: AspenTech SSE Portfolio and OSDU

In this presentation we will provide an overview of AspenTech’s strong commitment to the success of the OSDU Data Platform, and demonstrate how users of AspenTech solutions for Formation Evaluation, Seismic Interpretation & Classification and Reservoir Modeling can import, stream, share and publish data directly from and to an OSDU instance from within our applications. The Open Group OSDU Forum is an industry-led, collaborative approach to solving problems of inter-vendor interoperability, and vendor-agnostic data storage. AspenTech supports this important industry initiative by connecting our applications to OSDU data repositories and providing expertise and open source DMS code to the OSDU platform. This presentation will show the parallel development initiatives of our new digital platform proposal on top of OSDU.

Presented by Gerardo González

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Wednesday 10:00 Thursday 13:30

Fast Seismic Interpretation Workshop

Featured technology: Aspen SeisEarth™

Join our workshop, where you can learn to extract much more from seismic data. In this session you will learn how to use the AspenTech seismic propagator and interpretation workflows to perform geobody extractions. Generating seismic products has never been so easy! Come and have fun learning, places are limited.

Presented by Leandro Machado/Thiago Cuzzatti

aspentech.com at SGBF

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