Cost-efficient CO2 monitoring technology (Task 12)

Reliable CO2 monitoring is a necessity for safe CO2 storage, but monitoring of a storage site is potentially very expensive. The main ambition of Task 12 is to develop and demonstrate monitoring technology which will enable safe operation in compliance with laws and regulations in the most cost-efficient manner.

Reliable CO2 monitoring is a necessity for safe CO2 storage. Industry operators have to comply with regulatory requirements for safety and also need monitoring for predictable and cost-efficient operation. Monitoring of a storage site is potentially very expensive. The main ambition of Task 12 is to develop and demonstrate monitoring technology which will enable safe operation in compliance with laws and regulations in the most cost-efficient manner. This will benefit our industry partners Equinor, Total, Lundin, Vår Energi, and Wintershall, and other potential CO2 storage operators. 

To ensure optimal industry relevance and the highest possible relevance for the Northern Lights project (the carbon storage project of Equinor, Shell, and Total) on the Norwegian Continental Shelf, the industry will be closely involved through the lifetime of the Task. Involvement of vendors with expertise from oil and gas monitoring will also be important, and we will seek to have a dialogue with regulators.

Most of the monitoring activities in this Task are related to both Deployment Cases, since similar geophysical monitoring technologies are expected to be used in both cases.

Results 2020

In 2020, effort was made to disseminate important recent results from the CO2 monitoring task of the NCCS centre.

The Bayesian Rock Physics Inversion technique (completed and demonstrated in 2019) and its application to Sleipner data was thoroughly described in a paper (“Combined geophysical and rock physics workflow for quantitative CO2 monitoring”) for the International Journal of Greenhouse Gas Control (IJGGC) that was accepted for publication at the end of the year. Similarly, another IJGGC paper, “Assessing the value of seismic monitoring of CO2 storage using simulations and statistical analysis”, summarizing previous work on a value-of-information assessment workflow was accepted for publication at the very end of the year.

At the beginning of the year, four abstracts were also sent to the GHGT conference, which was unfortunately delayed until 2021. All abstracts were accepted and draft papers have been written related to each of these topics.

One of the papers describes the current status of work done on combining monitoring data and reservoir simulations of CO2 storage sites for improved understanding of a storage site. The method, based on a flexible modelling framework in the open source Matlab Reservoir Simulation Toolbox (MRST), allows optimization of CO2 storage modelling to any combination of observed monitoring data. It has been applied to the new, layered, Sleipner benchmark model, which was optimised to fit plume outlines, gravity monitoring data and CO2 saturations inferred from joint full waveform and rock physics inversion with promising results.

Another GHGT draft paper describes how SINTEF's optAVO method can be used to map the extent of the CO2 plume and provide an estimate for seismic parameters for a synthetic Sleipner case. Using the results (a P-wave model) of the optAVO as an initial model for Full Waveform Inversion (FWI) was seen to significantly improve the final FWI results.

The two other GHGT draft papers focused on monitoring at Smeaheia; one about application of a workflow for baseline quantitative characterisation using synthetic and real data from Smeaheia and one about a feasibility study on marine CSEM monitoring of CO2 flow along the Vette Fault. This latter study is the first of its kind as the only previous evidence of the efficiency of CSEM for detection of CO2 flow through faults/fractures was made through a laboratory test. The work has resulted in knowledge about how the CSEM data may interact with CO2 flow through the Vette Fault. Issues for which the CSEM technique should be improved were also identified.

Aerial view of the Svelvik CO2 Field Lab with injection (#2) and monitoring wells (M1-M4) marked. The loops with fibre optic cables (several different commercial and research types) are shown yellow with tongues indicating how the cables also go down into the wells.
Aerial view of the Svelvik CO2 Field Lab with injection (#2) and monitoring wells (M1-M4) marked. The loops with fibre optic cables (several different commercial and research types) are shown yellow with "tongues" indicating how the cables also go down into the wells.

Two successful webinars were carried out in 2020, both with a focus on more novel and unconventional technologies for CO2 monitoring. The spring webinar summarized work done within the task related to "A machine learning based monitoring framework for CO2 storage". The approach is based on integration of reservoir modelling, geophysical monitoring, and decision-making theory, and it was shown that a neural network can be trained to optimize geophysical data acquisition in terms of its value for verification of site performance. This is a first step towards a novel AI-based technique to support the decision-making process related to cost-efficient MMV. The autumn webinar, with nearly 230 registered, had a more general look at "Safe and cost-efficient CO2 storage: Emerging monitoring technologies" with an overview of what we see as promising future techniques. An informal survey on the view of the participants was also carried out.

In addition to this survey of emerging technologies, two smaller studies were carried out in 2020 to investigate the potential of using ECCSEL infrastructure in future work within the monitoring task.

The first investigated the possibility and usefulness of performing measurements of elastic and electric parameters at controlled laboratory and test site conditions in order to explore the physics and the interrelationships of these parameters as functions of saturation, pressure and temperature. Such measurements will contribute to calibrating rock physics models and would consequently result in more reliable interpretation of monitoring data. Several potential research tasks were suggested. Similarly, a study of potential research efforts on development and testing of fibre-optic (DAS/DTS/DSS) technology was carried out. This emerging monitoring technology is still not properly explored for CO2 monitoring purposes.

The recently upgraded Svelvik CO2 Field Lab has several monitoring wells instrumented with various types of optical fibres and offers great possibilities for such studies. A number of potential research tasks and spin-off projects have been suggested for the next few years in NCCS.

Word cloud summarizing webinar particpants answers to What are the most promising emerging technologies for CO2 monitoring. (right) Boston square matrix showing webinar participants answers to Estimate potential impact of technology when deployed and the research effort needed to get there.
Word cloud summarizing webinar particpants answers to "What are the most promising emerging technologies for CO2 monitoring". (right) Boston square matrix showing webinar participants answers to "Estimate potential impact of technology when deployed and the research effort needed to get there".

Main results 2019

Reliable monitoring of a CO2 storage site is essential for safe and efficient operation, as well as for public acceptance. By carefully monitoring the site before, during, and after CO2 injection, the risk for very costly intervention, remediation, or site closure is significantly reduced. Such surveillance can potentially be very expensive. The main ambition of Task 12 is to develop and demonstrate monitoring technology which will enable safe operation in compliance with laws and regulations in the most cost-efficient manner.

During the year, we applied a newly developed approach for reservoir parameter estimation with uncertainty quantification (Bayesian Rock Physics Inversion) to Sleipner 2008 seismic data. We demonstrated how important reservoir parameters, such as CO2 saturation and reservoir pressure, can be estimated with a simultaneous assessment of uncertainty, providing essential operational information to the storage site owner. Initial studies also showed how the estimated reservoir parameters can be used to constrain and calibrate reservoir simulations of the Sleipner injection. This calibration enables improved prediction of the future behaviour of the storage site.

The development and testing of a compressive sensing technique for enhanced geophysical data acquisition and interpretation continued in 2019. This technique, which can help to reduce the need for dense (and expensive) seismic surveys, was succesfully verified for sparse subsets of Sleipner data.

Reliable and cost-efficient monitoring will be essential for the Northern Lights project. Task 12 developments like the ones described above will support the design of an optimal monitoring scheme. Another such example is how the research and development of Controlled Source Electro-Magnetics (CSEM), as a complement to seismic, could provide a more cost-efficient and accurate approach for quantitative CO2 monitoring. Based on synthetic Smeaheia data, a quantitative CSEM inversion study was successfully concluded in 2019 (see the figure). Results show that CSEM can be used to give accurate volume estimates.

For any future storage project, there is also a great value in the research efforts on value-of-information, which offer new ways for an operator to analyse and select optimal geophysical monitoring strategies. During 2019, a conceptual Smeaheia case was used to demonstrate how a novel method for value-of- information analysis, based on machine learning, can be used to determine the optimal way of detecting potential leakage from CO2 storage.

In 2019, we also initialised two spin-off projects (EM4CO2 and Tophole) for more detailed studies of two important topics. EM4CO2 investigates the use of electro-magnetic methods as a complement to seismic for more quantitative reservoir monitoring information. Tophole studies how the integrity of plugged and abandoned wells can be cost-effectively monitored to enable CO2 storage in regions with existing wells.

CO2 volume estimations from CSEM inversion results. Left: True model, Middle: Result with unconstrained inversion, Right: Result with constrained inversion.

Results 2018

Main Results

  • Smeaheia baseline geophysical models and rock physics models built using Gassnova seismic data (Fig. 1)
  • Sensitivity test of CO2 injection on seismic observables at Smeaheia
  • Initial sensitivity studies for use of CSEM at Smeaheia (Fig. 1)
  • Demonstration of joint rock physics inversion approach at Sleipner using CSEM and seismic 2008 datasets
  • Validation of compressive sensing strategy for improved cost-efficient imaging
  • New survey optimization strategy tested
  • Work on combined modelling-monitoring and "history matching" initiated
  • Evaluation of cost-saving potential of NCCS CO2 monitoring developments

Impact and innovations

  • First application of FWI to get most out of Gassnova's 3D seismic data at Smeaheia could become useful for Northern Lights project for reservoir seal characterization and monitoring planning
  • The compressive sensing approach can help to reduce the need for dense (and expensive) seismic surveys
  • Survey optimization technique and combined modelling-monitoring workflow will help to find cost-efficient ways of confirming site conformance during injection
Selected results from Task 12 in 2018. [top left] P-wave interval velocity model in depth for a subset of the Inline 1024 from Gassnova's seismic cube GN1101. [top right] P-wave velocity model derived from FWI for the subset of Inline 1024 (from Dupuy et al. 2018, to be published). [middle left] 2.5D true resistivity models for simulated injection at Smeaheia until 2045. [middle right] CSEM inversion results. [bottom] A survey optimization strategy was developed and tested for synthetic Sleipner CSEM case. Circles representing optimal lateral source position and sensitivity (area). Each source is used together with all five receivers (represented by red triangles).

Results 2017

The task focused on setting up synthetic Smeaheia geophysical models, on developing new approaches for efficient use of available data for quantitative CO2 monitoring, and on using a statistical value-of-information concept for cost-minimization of CO2 monitoring.

For Smeaheia, Statoil's CO2 injection simulations were used to build synthetic models of the subsurface acoustic velocity, resistivity, and density at different times during and after the injection. These models together with Smeaheia data provided by Gassnova will serve as very important input for targeted Smeaheia monitoring studies in the years to come in NCCS.

Work on quantitative CO2 monitoring at Sleipner led to promising results that was presented at several workshops and conferences and published in several journals. In total, six publications were produced.

Industry partners Statoil, Shell and Total, as well as vendor Quad Geometrics have contributed to the task and participated in a workshop in September. Late in 2017, EMGS confirmed that they want to join the task as a vendor.

Publications

Journal Publications

2018:

2017: 

Conference Publications

2018:

  • Bandlimited optimal AVO inversion for improved quantitative imaging of the CO2 Plume - A. Ghaderi, B. Dupuy, E. Querendez, P. Eliasson. GHGT-14, Melbourne
  • Estimating the impact of large-scale and sub-scale structural trapping on long-term CO2 plume migration in the Gassum Formation using seismic line data - O. Andersen, H.M. Nilsen, U. Gregersen, A. Sundal. GHGT-14, Melbourne
  • Optimized geophysical survey design for CO2 monitoring - A synthetic study - A. Romdhane, P. Eliasson. GHGT-14, Melbourne
  • Smeaheia baseline geophysical models - B.Dupuy, E. Querendez, A. Ghaderi, A. Romdhane, P. Eliasson. GHGT-14, Melbourne
  • Uncertainty quantification for CO2 monitoring methods applied to Sleipner and Smeaheia data - P. Eliasson, A. Romdhane. GHGT-14, Melbourne

Task leader

Jon Peder Eliasson

Senior Research Scientist
473 69 732
Name
Jon Peder Eliasson
Title
Senior Research Scientist
Phone
473 69 732
Department
Petroleum
Office
Trondheim
Company
SINTEF AS