Task 7: Field scale evaluation and history matching

These are the projects in Task 7.

Project title: Production optimization
Project manager: Geir Nævdal (IRIS)
Objective: The main objective of this project is to further develop robust optimization algorithms for efficient use in the petroleum production optimization problem. The secondary objectives are: Extension of ensemble-based production optimization to include IOR strategies (not only optimizing waterflooding). Investigation of how reduced order methods can reduce the computational effort needed (current workflows are computationally demanding due to the need for a large number of reservoir simulations)

Project title: Robust production optimization (PhD project)
Project manager(s): Reidar B. Bratvold UiS), Geir Nævdal (IRIS) and Aojie Hong UiS)
Objective: The main objective of this project is to develop robust optimization methods. The secondary objectives include: An optimal production strategy including geological uncertainties. How the decisions (optimal production strategies) may be different for robust optimization based on the geological uncertainties before and after history matching. (Geological uncertainties can be reduced by history matching). The impact of history matching on the results of robust optimization methods will be investigated through a Value-of-Information analysis.

Project title: Assemblage of different step size selection algorithms in reservoir production optimization(PhD project)
Project manager(s): Andreas S. Stordal (IRIS), Svein M. Skjæveland (UiS) and Yiteng Zhang (UiS)
Objective: The main objective of this project is to give a precise mathematical formulation of ensemble based optimization under geological uncertainty. The secondary objectives include: Improving the existing methodology using more sound mathematical insight. Understanding and improving the formulation of the objective function under uncertainty. Investigating the effect uncertainty has on several different parametrisations of the problem formulation.

Project title: Data assimilation using 4D seismic data
Project manager: Geir Nævdal (IRIS)
Objective: The primary objective of this project is to include 4D seismic data in ensemble based history matching for full fields. The secondary objectives include: Establishing real field(s) and gathering data required. Investigating in which form of 4D seismic data is most suitable for inclusion. Developing suitable rock physic model(s). Uncertainty quantification of the seismic data. Handle the big data amount of seismic data.

Project title: Interpretation of 4D seismic for compacting reservoirs
Project manager: Geir Nævdal (IRIS)
Objective: The main objective of this project is to address the extra complexity of compacting reservoirs when including 4D seismic data in history matching. The secondary objectives are: Working towards solving this problem with a data set from ConocoPhillips (Ekofisk). Initially we will focus on interpreting 4D AVO seismic data for updating saturations, pressures and porosities. (In this case the porosity is changing due to the effect of compaction.) In the second step we will use the interpreted data for ensemble-based history matching.

Project title: Data assimilation using 4-D seismic data (PostDoc TNO)
Project manager: Philippe Steeghs (TNO)
Objective: The main objective of this project is to improve and evaluate TNO’s ensemble-based history matching workflow in an extensive field case study. Moreover, the project will demonstrate the potential of the proposed method for 4D seismic monitoring and history matching.

Project title: 4D seismic and tracer data for coupled geomechanical/reservoir flow models
Project manager: Jarle Haukås (Schlumberger)
Objective: The main objective of the project is to investigate rational methods for building and updating coupled fluid flow/geomechanical models. The secondary objectives include: Linking 4D seismic observations to stress exchange in the reservoir and surrounding rock. Including the impact of faulted and fractured rock in history matching

Project title: Elastic full-waveform inversion (PhD project)
Project manager(s): Wiktor Weibull (UiS) and PhD student
Objective: Accurate and well-resolved estimates of the subsurface parameters from seismic data are essential for both exploration, as well as increased recovery of oil and gas reserves. This is particularly true as exploration moves towards subtler traps in complicated geological environments. At the same time, the ability to detect small changes in elastic parameters due to fluid substitution can greatly aid the development of increased oil recovery strategies. Full waveform inversion (FWI) is a well-known method for estimating subsurface parameters from seismic data. FWI can be used with single vintage seismic data to improve knowledge of the subsurface, or it can be used to estimate changes in subsurface parameters in a time-lapse fashion from 4D seismic data. This makes this technology well adapted for both the exploration and production stages of the petroleum value chain. Elastic FWI can be used to estimate both P-wave and S-wave impedances or their changes over time from multicomponent seismic data. There are still major challenges in applying FWI to field scale datasets. One problem is related to the high cost of the method. Another well known problem is the non-uniqueness of the problem. In terms of 4D seismic data, the major challenges are to reduce the artefacts introduced by repeatability errors and to include high enough frequencies in the inversion. Any attempt to use FWI must therefore tackle these challenges. In addition to developing strategies to tackle the above mentioned problems, we have also set the following key objectives: (1) To develop and test statistical methods of inference and to compare these with deterministic methods; (2) To use elastic FWI to estimate changes in elastic properties due to production from multicomponent seismic data acquired in permanent reservoir monitoring installations (PRMs). These estimated time-lapse changes will be compared with conventional approaches based on time-shift and time-strain measurements.


  • Arne Stavland

    Task 1: Core scale

    Task leader: Arne Stavland, IRIS

    The aim of this task is to design novel experiments on core scale and develop models that capture the transport mechanisms observed. The deliverables of this task will be chemical systems that can improve the microscopic and microscopic sweep on clastic and chalk fields.

    Read more about the projects in Task 1 here

  • Udo Zimmermann

    Task 2: Mineral fluid reactions at nano/submicron scale

    Task leader: Udo Zimmermann, UiS

    The research is focused on rock-fluid interactions when injecting fluids into rock formations either clastic or chemical sedimentary rocks. We deliver methods in the field of electron microscopy, Raman spectroscopy, specific surface area measurements and X-Ray Diffraction for further investigations of EOR related experiments. The geology of the hydrocarbon bearing formations plays a significant role.

    Read more about the projects in Task 2 here

  • Espen Jettestuen

    Task 3: Pore scale

    Task leader: Espen Jettestuen, IRIS

    The focus in this task is to study the interplay between fluid transport, mineral reactions and oil recovery in reservoir rocks at pore scale. The main aspects are to identify the mechanisms that influence transport and reactions on the pore scale using experiments and numerical modeling, and then to evaluate if these mechanisms are important on the core scale.

    Read more about the projects in Task 3 here

  • Aksel Hiorth

    Task 4: Upscaling and environmental impact

    Task leader: Aksel Hiorth, UiS/IRIS

    The main objective is to translate the knowledge we have about EOR processes on core scale to field scale. The deliverables from this task will be simulation models and work flows that can be used to design IOR operations and interpret IOR implementations.

    Read more about the projects in Task 4 here

  • Tor Bjørnstad

    Task 5: Tracer technology

    Task leader: Tor Bjørnstad, IFE

    The objective is the development of tracer technology to measure reservoir properties and (changing) conditions during production. The most important condition is the (remaining) oil saturation, either in the flooded volume between wells (interwell examinations) or in the near-well region out to some 10 m from the well (single-well huff-and-puff examinations).

    Read more about the projects in Task 5 here

  • Robert Klöfkorn

    Task 6: Reservoir simulation tools

    Task leader: Robert Klöfkorn, IRIS

    The primary objective of this task is to advance the state-of-the-art of modeling and simulation in context of reservoirs. Such advance is needed to cope with the challenges arising from scientific questions and targets of The National IOR Centre of Norway.

    Read more about the projects in Task 6 here

  • Geir Nævdal

    Task 7: Field scale evaluation and history matching

    Task leader: Geir Nævdal, IRIS

    We are focusing on history matching using 4D seismic data, tuning reservoir parameters to obtain reservoir models that are matching the actual observations. We are using ensemble based methods, running with a set of different realizations of the parameter set and use statistical methods to tune the parameters. The outcome is a set of reservoir simulation models that are aligned with actual observations.

    Read more about the projects in Task 7 here