NORSAR Seismic Modelling NORSAR-3D NORSAR-2D VelRock 14/04/2017

NORSAR offices in Norway This is the location of NORSAR at Olso and Bergen, Oslo being the ”mother site”. 14/04/2017

NORSAR vs. UiB Agreement on cooperation between NORSAR and the University of Bergen. NORSAR was providing Institute of Solid Earth Physics with software for use in research projects, theses and education, includes commercial tools such as NORSAR-2D, NORSAR-3D, VelRock, HybriSeis, and prototype software for special studies. NORSAR is willing to extend this to include the newly formed Department of Earth Science and the CIPR. 14/04/2017

NORSAR-2D: Ray Modelling Two-point tracing Interactive Robust User-friendly 14/04/2017

NORSAR-3D: Ray Modelling Wavefront Construction (*) Open models Fits for PSDM Network of computers (*) NORSAR is the developer of Wavefront Construction! 14/04/2017

NORSAR-3D: Illumination Various Maps Simulated Migration Amplitudes Projects On-going research 14/04/2017

Rock Physics Modelling Analysing and predicting how different reservoir properties of porous rocks affect the seismic properties. VP = 2.6 km/s VS = 1.4 km/s  = 2.2 g/cm3 Rock Physics lithology fluids porosity permeability  VP: P-velocity VS: S-velocity A basic tool for the geophysical reservoir model building is the rock physics modelling system – called VelRock - integrated in the NORSAR-2D and -3D packages. In this system various rock properties in the reservoir (like lithology, pore fluids, porosity, permeability, etc) can be represented, and these rock models can then predict how different reservoir properties influence on the seismic properties, that is velocities, densities, (and attenuation factors). 14/04/2017

VelRock and N2D/N3D VelRock rock models can be used in N2D/N3D 14/04/2017

HybriSeis Modelling of Local Target In the HybriSeis method we combine ray tracing in the overburden with finite difference modelling in a local reservoir zone where the parameters are to be varied to form different scenarios. This technique first calculates by ray tracing Green’s functions for the overburden from shot/receiver positions to a coupling surface at the top of the target. The Greens functions bring the wave field from shot to target and from target to receivers in the simple part of the model where ray theory is a good approximation. Since the overburden is unchanged, this needs to be done only once. The expensive FD modelling in the complex reservoir zone can be restricted to a small box, saving a lot of computer time. This modelling must be done once for each scenario. 14/04/2017

Seismic Wave Simulation Tools Ray methods (standard software) 2D/3D Normal incidence ray tracing (zero offset unmigrated) 2D/3D Image ray tracing (zero offset migrated) 2D/3D Common shot (offset HSP/ VSP/OBC) 2D/3D Green’s functions 2D Anisotropic Ray Mapping Special methods (internal software) 1D Reflectivity (offset) 2D/3D Eikonal Method 2D Finite Difference 2D/3D Migrated Amplitudes 2D/3D HybriSeis Having established the overburden and a number of reservoir models, that is a number of scenarios, we have several tools for seismic wave simulation to produce various types of seismic responses. The choice of which tool to use depends on the complexity of the model and the problem to be analysed. In our standard software we have 2D and 3D normal incidence and image ray tracing, common shot ray tracing including surface seismics, VSP and OBC, Green’s functions for Kirchhoff methods and PSDM, and anisotropic ray mapping.   In our internal software we have also 1D reflectivity modelling, 2D/3D first arrival methods, 2D finite difference methods, and a new ray based method for simulating migrated amplitudes. For simulating seismic waves in models with a common overburden and many local reservoir scenarios, we have developed a new method called HybriSeis. 14/04/2017

Applications of NORSAR Software Typical tasks Model based analysis of well log data. Model based analysis of velocities measured on cores. Structural and velocity macromodel building. Geophysical reservoir model building. Modelling of seismic responses. Model based processing and analysis of seismic data. Special tasks Time-lapse feasibility studies. AVO modelling. Survey planning. Identification of multiples and peg-legs. Greens functions for PSDM. Amplitude and illumination maps. Reflector-oriented amplitude recovery (ROAR). 14/04/2017

NORSAR-3D: Structural and Velocity Model Building 3D Wavefront construction

Possible Input Data Interpreted horizons (time, depth). Pre-calculated interval velocities (const., grid, cube). Stacking velocities, migration velocities. Checkshots. Well log data (P-velocity, S-velocity, density). Petromarkers. 14/04/2017

Example: Undershooting of Salt Dome Shot  Receivers  Salt diapir  Targets (gas pockets)  14/04/2017

Ray Paths and Reflection Points Number of arrivals/receiver Reflection Points 14/04/2017

Example: Illumination of Gas Caps 14/04/2017

Marine Survey 14/04/2017

Wavefront Construction Wavefronts  Raypaths  14/04/2017

Bulk Modelling Depth model built from depth grids and velocity grids. Ray modelling done by wavefront construction. 4011 shots simulated in parallel on 10 workstations in a few hours. A total of about 24 million events for PP reflections from the target horizon (Top Reservoir) was found. 14/04/2017

Illumination Density Map {Event counts}/{nominal fold(30)} 14/04/2017

Min. Incidence Angle in CRP 14/04/2017

Max. Incidence Angle in CRP 14/04/2017

Amplitude along Target Horizon 14/04/2017

Real Model Example The example to follow was presented by Børge Rosland (Seispro) and Geir Drivenes (Enterprise Oil) in the paper “Large Scale 3D Seismic Modelling in Exploration”, paper no. C-42, EAGE meeting, Glasgow, 2000.

Geometry Model The first 5 reflectors are relatively flat. The BCU reflector and pre-BCU reflectors are complex. The P-velocity is shown on the left. 14/04/2017

Model and Marine Survey Every 2nd shot lines Target Horizon Receivers 14/04/2017

Bulk Modelling Modelled shot records, ~ 40 million traces. P-P reflection data from two reflectors: one smooth Cretaceous reflector. one complex pre-BCU reflector. Single Shot Footprint Pre-BCU Reflector 14/04/2017

Illumination Density Map About 25 000 000 reflected rays Illumination Density Map: Number of reflection points in bin cells (50x25m) on the target horizon Highly-curved parts of the reflector are strongly illuminated 14/04/2017

Real vs Modelled Amplitudes Migrated Seismic Data Reflection Amplitude Migrated Modelled Data Reflection Amplitude 14/04/2017

Migrated Modelled Data Reflection Coefficient Modelled Amplitudes Migrated Modelled Data Reflection Amplitude Normal Incidence Reflection Coefficient 14/04/2017

Integrated Modelling Based Reservoir Analysis NORSAR tools for rock physics and advanced seismic wave simulation

Gullfaks Time Lapse Data -1985 and 1996 OWC Top Res. We’ll introduce you to the NORSAR modelling capabilities simply by showing you these data from a time lapse study on the Gullfaks field on the Norwegian shelf, provided by Statoil Research Centre. The picture shows sections from two 3D surveys, shot in 1985 and 1996. A horizontal event in the reservoir formations on both sections was interpreted as a fluid contact, that was observed to be substantially weakened throughout the 11 years of production. The top reservoir reflection have also been weakened. Are these changes consistent with a reduced oil saturation? OWC Top Res. Courtesy of Statoil 14/04/2017

Integrated Rock Physics and Seismic Modelling Seismic response Well log data Mineralogy Geological model Fluid simulations Seismic data Lab. data In our ‘integrated modelling scheme’ we try to combine rock physics and seismic modelling within a physically consistent framework, where different types of observations or hypotheses can be entered – to produce a modelled seismic response. 14/04/2017

Problems of integrated modelling Complexity of model representation, with parameters that may not have an easy physical interpretation. No generally applicable theory for all problems. Processes that may be difficult to quantify. Microscopic properties may be important for large-scale properties. Different sources and scales of data may cause inconsistencies and problems. 14/04/2017

Rock Physics Models  VP = 2.6 km/s VS = 1.4 km/s  = 2.2 g/cm3 Analysing and predicting how different reservoir properties of porous rocks influence on the seismic properties. VP = 2.6 km/s VS = 1.4 km/s  = 2.2 g/cm3 Rock Physics lithology fluids porosity permeability  VP: P-velocity VS: S-velocity A basic tool for geophysical reservoir model building is the rock physics modelling system – called VelRock - integrated in the NORSAR-2D and -3D packages. Here various rock properties in the reservoir (like lithology, pore fluids, porosity, permeability, etc) can be represented, and these rock models can then predict how different reservoir properties influence on the seismic properties, that is velocities, densities, (and attenuation factors). The rock models may be used for predicting geophysical properties, in various sensitivity analyses and feasibility studies, and for setting the properties of the geophysical reservoir model. 14/04/2017

Factors Influencing on Seismic Velocities brine shaley sand oil velocity velocity velocity gas sand shale pore fluid porosity lithology velocity velocity velocity pore pressure confining pressure effective pressure The different rock property factors influence seismic velocities in a lot of ways. Here we just show schematically how P-velocity may be typically affected by: pore fluid, porosity, lithology, pore pressure, confining pressure, effective pressure, age/depth, temperature and cementation. Even if the variation with each factor may seem simple, the whole system forms complex interactions that is taken care of by the rock physics modelling tool VelRock. T 3 velocity T 2 velocity velocity T 1 age / depth temperature cementation 14/04/2017

Seismic Response of Reservoir Properties Rock physics is the key for understanding how geological properties are manifested in seismic observations, through bright spots, AVO characteristics etc. Rock physics modelling allows for predicting seismic rock properties at other physical conditions than observed in wells or by laboratory measurements. Improved understanding about how rock properties influence on seismic properties and seismic response is vital to the feasibility of seismic monitoring of hydrocarbon reservoirs. Integrated rock physics and seismic modelling provide physically consistent tools for identifying and quantifying the important reservoir properties and predict their sensitivity to changes. 14/04/2017

Multi-well Log Data Sorting and Quality Control rfl=1.0 rfl=1.0 Well log data provide valuable information about the target formations. But the data must be carefully edited and checked for consistency. This should include multi-well sorting and crossplotting. Here observation of P-velocities (above) and densities (below) for brine- and oil-saturated sands from 3 wells are plotted against porosity. The density trends of the brine- and oil-saturated data are very similar considering that the fluid densities are quite different, 1.02 vs. 0.67. This may be caused by drilling mud invasion and should be taken into account when using the data. 14/04/2017

Rock Model Calibration We will use the quality checked and corrected sonic and density data to calibrate rock models for the target formations. Such models give consistent relationships between important parameters such as porosity, lithology and pore fluid. Rock model variables: Porosity, Lithology, Pore fluid. 14/04/2017

Model Based Analysis of Well Log Data Use calibrated rock physics models for processing well log data, and predicting log properties. Possible to combine with AVO analysis of modelled effects. Types of analyses: Prediction of S-wave velocity. Prediction of impedances, elastic moduli etc. Prediction of geophysical properties assuming other saturating fluids (fluid substitution). Corrections for drilling mud invasion. Lithology and fluid sensitivity analysis. Property cross-plotting analyses (QC and diagnosis). Pressure effect sensitivity analysis (using core measurements). Integration of fluid simulation results. Upscaling and homogenization. 14/04/2017

Prediction of S-wave Velocity Logs Castagna Rock model Log data We may apply the calibrated rock model for prediction of S-wave velocity logs from P-velocity and density measurements. Shown is a comparison with the logged S-velocity (in black), rock model predicted S-velocity (in blue) and an empirical S-velocity prediction (in red). Note that the logged S-velocity was not used when calibrating the rock model used here. We also see that the rock model predictions well represents the logged P-velocity and density (top figure). 14/04/2017

Model Derived from Interpolation Between Wells 14/04/2017

Grid of reservoir properties 14/04/2017

Integration with Fluid Simulations Sgas Sgas DSg DvP DZP 14/04/2017

Rock Physics Modelling of Fluid Effects 0.25 km/s 0.1 g/cm3 Another very important aspect is the modelling of fluid effects – here we have predicted P-velocity and density in a zone in the well for various fluid substitutions: a typical gas-, oil- and brine-zone. The fluid effect may be analysed seismically using 1D, 2D or 3D modelling tools. 14/04/2017

AVO Modelling of Fluid Effects Brine Saturated Gas Saturated 14/04/2017

Reservoir properties and amplitude variations Lateral change in fluid composition and shale contents. Modelled seismic response from NIP tracer 14/04/2017

Effect of Offset, Lithology and Saturating Fluid Homogeneous reservoir properties Vertical trend in lithology GOC GOC Zero Offset Section OWC 2km Offset Section 14/04/2017

Gullfaks 2D Reservoir Models Scenario 1 : SOil=0.9 Scenario 2 : SOil=0.2 Having available complete velocity models and an efficient Green’s function calculation process it is quite straightforward to do Prestack Depth Migration of the HybriSeis data. These figures show PSDM images for the two example scenarios. HybriSeis PSDM All offsets 14/04/2017

Schematic View of a Time-lapse Modelling Loop Rock physics Geological model Seismic modelling Seismic data Fluid flow simulations Inversion 14/04/2017

Reservoir Target Model Building 14/04/2017

Modelling Based Ananlysis 14/04/2017