Time lapse VSP monitoring of small scale injected CO2 in the Frio formation, Texas, USA

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Examensarbete vid Institutionen för geovetenskaper ISSN 1650-6553 Nr 275

Ershad Gholamrezaie

Uppsala universitet, Institutionen för geovetenskaper Examensarbete E1, 45 hp i Geofysik

ISSN 1650-6553 Nr 275

Tryckt hos Institutionen för geovetenskaper, Geotryckeriet, Uppsala universitet, Uppsala, 2014.

Time Lapse VSP Monitoring of Small scale Injected CO in the Frio Formation, Texas, USA

²

Time Lapse VSP Monitoring of Small scale Injected CO in the Frio Formation, Texas, USA ²

Carbon dioxide (CO2) emission is one of the most significant reasons of global warming. Carbon Capture and Storage (CCS) is a high level technology used in recent decades to reduce the emission rate of carbon dioxide in the atmosphere.

One of the principal methods in CCS is to store the captured CO2 in deep and suitable geological structures.

In October, 2004, sixteen hundred tons of supercritical CO2 were injected at a depth of 1530 meters in the Frio formation sandstones in south of Texas, USA.

Time lapse monitoring of VSP data was one of the chosen geophysical techniques to detect the small scale injected CO2 in the Frio test project. A pre- injection survey had been done in July, 2004 and the same data acquisition was repeated 45 days after the injection as a post injection survey.

In this research, time lapse data processing steps were applied to the VSP data and final results successfully detected the injected CO2 by identifying the changes in reflection amplitudes over time at the injection depth. Additionally, synthetic models were produced and compared with real models which were in accordance with each other.

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Examensarbete vid Institutionen för geovetenskaper ISSN 1650-6553 Nr 275

Ershad Gholamrezaie

Time Lapse VSP Monitoring of Small scale Injected CO in the Frio Formation, Texas, USA ²

Supervisor: Christopher Juhlin

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Abstract

Carbon dioxide (CO2) emission is one of the most significant reasons of global warming. Carbon Capture and Storage (CCS) is a high level technology used in recent decades to reduce the emission rate of carbon dioxide in the atmosphere. One of the principal methods in CCS is to store the captured CO2 in deep and suitable geological structures.

In October, 2004, sixteen hundred tons of supercritical CO2 were injected at a depth of 1530 meters in the Frio formation sandstones in south of Texas, USA.

Time lapse monitoring of VSP data was one of the chosen geophysical techniques to detect the small scale injected CO2 in the Frio test project. A pre-injection survey had been done in July, 2004 and the same data acquisition was repeated 45 days after the injection as a post injection survey.

In this research, time lapse data processing steps were applied to the VSP data and final results successfully detected the injected CO2 by identifying the changes in reflection amplitudes over time at the injection depth. Additionally, synthetic models were produced and compared with real models which were in accordance with each other.

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Acknowledgement

I would like to express a deep sense of gratitude to Thomas Daley and Lawrence Berkeley National Laboratory for providing the VSP data and allowing the publication.

My sincere gratitude and deep regards to Prof. Christopher Juhlin, my supervisor, for his exemplary guidance, monitoring and constant encouragement throughout the course of this thesis.

My sincere thanks also goes to Omid Ahmadi for permitting me to use his python code to plot the seismic data and his valuable comments.

I would also like to thank Dr. Alireza Malehmir, Dr. Hans Palm, and Dr. Monika Ivandic and all other members of Geophysics group at Uppsala University.

Last but not least, I would like to thank my parents for their unlimited love, uncon- ditional support, and great encouragement.

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List of Figures

1.1 The sources of energy . . . 1

1.2 Global Energy Demands . . . 2

2.1 The rate of the CO2 emissions by burning fuels . . . 3

2.2 Percentages of different sectors in producing CO₂ emission. . . 4

2.3 Processing steps in different methods of CO₂ capture. . . 5

2.4 Quality specification of transported CO2 . . . 6

2.5 Use of different storage methods by percentage. . . 6

2.6 Geological storage options . . . 7

3.1 VSP geometry . . . 8

3.2 Model of downgoing and upcoming waves . . . 9

3.3 Model of multiples in VSP survey . . . 10

3.4 The design and application of a shaping filter . . . 12

3.5 Amplitude recovery . . . 13

4.1 Location of the Frio pilot site . . . 15

4.2 Location of the injection well. . . 15

4.3 Stratigraphic units of the Gulf Coast . . . 16

4.4 Stratigarphic cross section of the Gulf Coast . . . 17

4.5 3D Seismic section in the Frio pilot site . . . 18

4.6 SP and Resistivity logs. . . 19

5.1 True scale model of geological sections in the injection zone . . . 20

5.2 Eight shot locations for VSP data acquisition. . . 21

6.1 Shot gather for source location 1 . . . 23

6.2 Shot static correction . . . 24

6.3 Downgoing and up coming wavefields . . . 24

6.4 Deconvolution and band pass filtering . . . 25

6.5 Two way travel time and NMO correction . . . 25

6.6 Final time-lapse plots of VSP data for shot 1 . . . 26

7.1 Calibration steps in Pro4D . . . 29

7.2 Shot gather for source location 1 after subtraction . . . 30

8.1 Velocity Model . . . 33

8.2 Ray tracing model and corresponding traveltime . . . 34

8.3 Source location 1 and corresponding synthetic model . . . 35

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List Of Abbreviations

CO₂ Carbon Dioxide

CCS Carbon Capture and Storage EIA Energy Information Administraion GHGs Greenhouse Gases

IER Institute for Energy Research

IPCC Intergovernmental Panel on Climate Change NMO Normal Move Out

SMF Spectral Matrix Filter SP Self Potential

SVD Single Value Decompositions TWT Two Way Traveltime

VSP Vertical Seismic Profiling

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1 Introduction

Consumption of energy is an inseparable part of our lives. We use different types of energy sources for industries, transportaion, food making, producing heat and light, communi- cations, and so on.

According to the annual reports from the Energy Information Administration (EIA)¹, fossil fuels are the major sources of energy. Petroleum, natural gas, and coal provide more than 80% of consumed energy in the world (figure 1.1).

Figure 1.1: The sources of energy

Use of fossil fuels as the source of energy releases carbon dioxide or CO2 which is the most important factor in global warming. The demand for energy is rising sharply due to the increase in the world’s population. Despite the increase of using environment friendly energy sources such as renewable energy, still the main source of the energy is the fossil fuels, and it cannot be replaced by other kinds of sources in the near future (figure 1.2 from IER² report). Fortunately, by technological developments, there is a way to decrease CO2 emissions called Carbon Capture and Storage (CCS).

In CCS projects, CO₂ is usually captured from industrial facilities and transported to injection sites by pipe lines or special vehicles, and then it is injected into deep and suitable underground structures such as gas and oil depleted reservoirs, saline aquifer, salt beds or caverns, and unmineable coal beds [14].

1http://www.eia.gov/aer

2www.instituteforenergyresearch.org

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Monitoring the injected CO₂ is one of the most important parts of CCS. Geophysical methods have essential roles in this. Methods such as 2D and 3D land seismic, Vertical Seismic Profiling (VSP), Crosswell, and seismic tomography are used to monitor the injected CO₂. Usually, these methods are used in time lapse mode, to track the changes before and after the injections.

In 2003, after studying twenty one potential saline aquifers in the United States of Amer- ica (USA), the Frio formation in Texas was chosen for 1600 tons of supercritical CO₂ test injection to study the evolution of the sequestration [5]. Time lapse VSP data acquisition was one the monitoring methods in the Frio project.

The main purpose of this thesis is processing and interpretation of the time lapse VSP data to monitor the small scale of injected CO₂ in a brine aquifer in the Frio formation in Texas, USA. Claritas, Hampson Russel, and MATLAB are the main software applications used for processing, interpretation, and forward modelling.

Figure 1.2: Global energy demands by sources, 2011 and 2040

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2 CO

₂

Capture and Storage (CCS)

Scientific studies show that the Earth’s surface is warming and the risk of climate changes is serious. According to the IPCC reports, the Earth’s surface temperature had an ascent by 0.6^◦C, during the Twentieth Century [2].

Modern life demands for consuming more fossil fuel energies, and it increases the rate of greenhouse gases (GHGs) in the atmosphere. CO₂ is one of the most effective GHGs in the trend of global warming. The EIA report predicts 35 billion metric tons per year of CO₂ emissions due to the burning fossil fuels by 2025, while the emissions were around 15 billion metric tons and 22 billion metric tons per year in 1970 and 2001, respectively (figure 2.1) [6].

Figure 2.1: The rate of the CO₂ emission by burning oil, coal, and natural gas.

As it is shown in figure 2.2 (from [2]) electricity generation, transport, industry, residen- tial, and agriculture have the majority share in producing global CO₂ emissions.

Available technology called Carbon Capture and Storage or CCS can help to reduce the CO₂ emissions. CCS is done in three main steps: Capturing, Transporting, and Storing.

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Figure 2.2: Percentages of different sectors in producing CO₂ emission.

2.1 CO

₂

Capture

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CO₂ can be captured in three common systems; post-combustion, pre-combustion, and oxy-fuel combustion. Figure 2.3 (from [16]) shows the processing diagram for these three capturing systems.

2.1.1 Post-combustion capture

In post-combustion capture, exhaust gases which have been produced by fuel combustion is guided to a chemical process that extracts CO₂ from the gas flow.

2.1.2 Pre-combustion capture

In this process, the fuel’s liqued phase is replaced by a gas phase and combined with air and steam. After some chemical converting, the final combination contains Hydrogen and CO₂, mainly. Afterward, CO₂ is extracted by a physical solvent.

2.1.3 Oxy-fuel combustion capture

Oxy-fuel combustion capture involves removing nitrogen from the air and tries using pure oxygen to mix with the fuel. Therefore, the exhaust gas is formed mostly by CO₂ and water vapour. CO₂ is easily separated by changing the H₂O phase to liquid.

2.2 CO

₂

Transportation

⁴

Transportation of CO₂ is the second main step in CCS projects. CO₂ can be transported by pipelines, ships, and railroad.

3All contents in this section has been extracted from [16].

4All contents in this section has been extracted from [14].

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Pipelines are the most common and safest method for transporting large volumes of CO₂ in the long distance movements. Due to the physical and chemical properties of CO₂ and its risk for public safety, transportation must be done under specific principles (Box in figure 2.4 [14]).

Figure 2.3: Processing steps in different methods of CO2capture.

2.3 CO

₂

Storage

Different methods are used for storing CO₂. Geological Storage, Ocean Storage, Benefi- cial Reuse, and Terrestrial Storage are various methods of CO₂ storage. Among all these methods, geological storage has the highest proportion in CO₂ sequestration (figure 2.5) [1].

The goal of geological storage is to trap CO₂ in suitable underground formations and structures, such as; depleted oil and gas reservoirs, deep brine aquifers, deep unminable coal seams, etc [3].

In addition, CO₂ injection has been using in enhanced oil and gas recovery which is categorised as a Beneficial Reuse method, but indeed these are geological structures which are used for CO2 sequestration. Figure 2.6 (from [14]) shows a schematic image of these suitable underground structures.

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Figure 2.4: Quality specification of transported CO2 by Canyon Reef Pipeline in Texas, USA.

Figure 2.5: Use of different storage methods by percentage.

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Figure 2.6: Schematic image of geological storage option for CO2sequestration.

3 Vertical Seismic Profiling (VSP)

3.1 Introduction

Land seismic surveys are the principal exploration seismology methods to study deep geological structures for different goals and targets. By advances in technology and utilizing suitable recording systems and seismic sources, underground structures can be monitored and imaged with 15 to 30 meters of vertical resolution. On the other hand, in near offset VSP surveys, due to the vertical receivers profile which can be located inside the target structures, the vertical resolution can be two or three times better than the vertical resolution in surface land seismic surveys [18].

In the Frio project, 1600 tons of CO₂ were injected which is considered as a small scale of injection comparing by other projects such as Sleipner CO₂ Injection in North Sea with 0.9 million tons of CO₂ injection per year⁵.

Considering the physical properties of CO₂ and the injection scale, the injected CO₂ in Frio should consist of a thin layer and probably would spread less than a few hundred meters from the injection point and with decreasing thickness. Monitoring a thin and small layer such as the injected CO₂ in Frio needs high resolution seismic surveys like borehole seismic methods. Land seismic surveys are almost unable to detect these thin

5http://www.globalccsinstitute.com/project/sleipner%C2%A0co2-injection

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and small layers in deep reservoirs. Therefore, time lapse VSP surveying was part of the acquired monitoring methods in the Frio project. In the next two sections (3.2 and 3.3), the concept and the standard processing steps of VSP will be reviewed.

3.2 The Concept of VSP

Vertical Seismic Profiling (VSP) is an exploration seismic method with a vertical recording profile which is installed in a well at different depths [8]. The differences between surface land seismic and VSP methods can be categorised as follow:

1. Different geometry, which leads to use of individual acquisition tools (specially for recording units), and some different and additional processing steps.

2. The ability of recording the down-going wave-field which is not possible in surface land seismic surveys[8].

The geometry of the VSP survey and the corresponding recording events for a simple three layer model is illustrated in figure 3.1(Modified from [9] after [11]). The black and red rays indicate first and multiple arrivals, respectively. These are the mentioned downgoing waves which are not recorded in surface land seismic methods. The direct reflection of two events (L1 and L2) is shown by yellow rays, and the green ray shows the multiple reflection. In addition, figures 3.2 and 3.3 represent the downgoing and upcoming wavefields and their multiples⁶. A reflector is assumed at the depth of 625 m, while the source is at the 400 m offset.

Figure 3.1: VSP geometry and corresponding recording image

6extracted and modified from www.youtube.com/watch?v=gCip6bOzFF8

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Figure 3.2: Model of Downgoing (top) and Upcoming (below) waves in VSP

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Figure 3.3: Model of multiple for Downgoing (top) and Upcoming (below) waves in VSP.

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3.3 Typical VSP Processing

By considering the targets of the survey, data acquisition parameters, types of the recording well, and other factors, various steps and methods of VSP data processing can be applied to the data set. By some adjustment on land seismic processing methods, we can use the same processing methods on VSP data [12].

Lee and Balch[12], reviewed general computer processing steps of VSP data sets:

3.3.1 Editing

Basic quality control is applied trace by trace to find the noisy and unacceptable traces and remove them from the data. Further more, some other sorting and pre-processing methods can be including in this step.

3.3.2 Stacking

Due to the weakness of some seismic sources, several shots are generated at one shot point. By stacking these shots, the signal to noise ratio (S/N) will be improved.

3.3.3 Shot Static Correction

Using buried seismic sources may affect the arrivals and reflections times due to the changes of the source depth. Calculating the time differences of various shot depth and applying them to the data would correct the time variations.

Assume L as the horizontal offset between shot holes and recording well, d₁ and d₂ as the depth of two different shots ∆d = d₂− d₁, H as the depth of the receiver, V as the mean velocity of the media between source and the receiver, and T₁ and T₂ as the corresponding time for the first arrivals for shots at d₁ and d₂, respectively. Afterward, the static time shift can be calculated by ∆T = T₂− T₁.It is possible to calculate ∆T , just by considering the data from the first shot, as follow;

∆T = pL²+ (H − d₂)²−pL²+ (H − d₁)² V

= T₁

pL²+ (H − d₂)²−pL²+ (H − d₁)² pL²+ (H − d₁)²

!

= T₁

pL²+ (H − d2)² pL²+ (H − d₁)² − 1

!

= T₁



 q

L²+ (H − (d₁ + ∆d))² pL²+ (H − d₁)² − 1





= T₁ s

1 + ∆d²+ 2∆d(d₁− H) L²+ (H − d₁)² − 1

!

= T₁ s

1 + ∆d(∆d + 2d₁− 2H) L² + (H − d₁)² − 1

!

(3.1)

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3.3.4 Band Pass Filtering

Systematic noise such as Stoneley waves along with additional random noise can be filtered by analyzing the frequency and applying the suitable frequency band pass filter, which leads to the enhancement of the signal to noise ratio.

3.3.5 Shaping Filter

Usually, due to the limitation on the length of active receiver profile in recording wells, it is not possible to cover the entire desired recording depth by one shot, therefore, several shots at the same location are used.

The form of the waves from these shots is not always similar and this contrast will have an effect on data during processing. To avoid it, a relevant shaping filter is designed from a standard wavelet and convolved with the recording wavelets which leads to the data to being similar (figure 3.4 [12]).

Figure 3.4: The design and application of a shaping filter

In figure 3.4 (from [12]), (a) is the main wavelet, recorded at a certain depth, (b) is the source monitor recording for the same depth and (d) is the standard wavelet. (c) is the shaping filter which has been produced by comparing (b) and (d), and finally, (e) is the result of the convolution of (a) and (c). Differences between original wavelet and the final wavelet are really noticeable.

3.3.6 Amplitude Recovery

Seismic amplitude in VSP is a function of depth and time, due to the spherical divergence, inelastic attenuation, decay of the wave energy, upcoming waves, acquisition geometry, and receiver imposed gain.

The following equation can recover the amplitude decay, where R is the arrival time,

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c is the scaling constant, and α is the absorption coefficient;

ce^−αR

R (3.2)

By using the least square method, the first arrivals amplitude is fitted to the above function which results to a corresponding amplitude exponential curve of first arrivals amplitude. The difference between the observed amplitude and the exponential curva- ture, will be the compensative amplitude and will recover the amplitude decay of the VSP data (figure 3.5 from [12]).

Figure 3.5: a) The first arrivals amplitude and the corresponding curve of (ce^−αR)/R. b) The compensative amplitude which is the difference of observed and least square curves

3.3.7 Wavefield Separation

As previously mentioned, recorded VSP data include both downgoing and upcoming wavefields. Separation of these wavefields is one of the most important steps in VSP processing sequences, which is really useful in further processing stages. The suitable deconvolution design and the quality of the final seismic image are highly dependent on this phase.

Lee and Balch[12] introduced velocity filtering as the tool of wavefield separation, nev- ertheless, other efficient methods can be substituted for the velocity filtering. Mari,

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Glangeaud and Coppens[13], discussed these methods and classified them in two major groups;

1. Approaches which need flattening of the first arrivals time, some of which are; sum and difference filter, median filter, wiener filter,and single value decompositions (SVD)

2. Approaches without flattening, such as; spectral matrix filter (SMF), parametric methods, and velocity filtering.

3.3.8 Deconvolution

By designing the deconvolution on downgoing wavefields (due to the stronger seismic energy in downgoing waves) and applying it to the upcoming wavefields, the multiple events either are eliminated, or at least reduced.

3.3.9 Seismic Imaging

With considering the type of the VSP, the acquisition geometry, and the target of the survey, further processing steps will be done on the data set to make the final seismic image. Some of these additional sequences include; two way travel time, normal move out (NMO) correction, stacking, and migration.

4 The Frio site background

4.1 Location

The injection well was drilled at 29^◦59⁰24.36⁰⁰N and 94^◦50⁰39.84⁰⁰W in geographic co- ordinate system [10]. The pilot site is located 9 kilometres southwest of Liberty and 8 kilometres southeast of Dayton, and around 100 kilometres from the Gulf of Mexico in the state of Texas, USA (figure 4.1 and 4.2).

4.2 Geology

According to previous studies [7, 17, 15, 10], the Frio formation is divided in three major parts; Upper Frio, Middle Frio, and Lower Frio, with the age of late Oligocene. The Frio formation is a sedimentary structure due to the progradation activities. It is partly covered by a transgressive marine shale formation called Anahuac (figure 4.3 from [10]).

The Frio formation has maximum thickness between the depth of 1400 and 2000 meter, the zone of CO₂ injection. The usable water base is approximated at the depth of 750 meter in a safe interval from the injection horizon (figure 4.4 from [10]).

Figure 4.5 (from [10]) illustrates a seismic section that encompasses the Frio pilot site and the injection well. The porosity log is also marked in the section and represents the Frio formation. Moreover, the South Liberty salt dome and other cited stratigraphic units are observed.

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Figure 4.1: Location of the Frio pilot site in USA.

Figure 4.2: Location of the injection well.

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Figure 4.3: Stratigraphic units of the Gulf Coast

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Figure 4.4: Complex stratigraphic cross section profile in the Gulf Coast with 200 km long, in the NW-SE direction.

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Self Potential (SP) and resistivity logs indicate the mentioned stratigraphic units (figure 4.6 from [10]). According to these logs and previous geological studies, the Frio formation is a sandstone and shale zone at the depth of 1494 meter with 490 meter thickness, overlies the Vicksburg & Jackson shale group and is covered by Anahuac, the 77 meter thick dominate shale formation [10].

Figure 4.5: 3D Seismic section and porosity log in the Frio pilot site.

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Figure 4.6: SP and Resistivity logs.

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5 VSP Data Acquisition at the Frio Site

In 2003, after studying twenty one potential saline aquifers in the USA, the Frio formation in Texas, was chosen for a small scale CO₂ test injection. During ten days in October, 2004, sixteen hundreds tons of supercritical CO2 with 150 bar downhole pressure and 55^◦C downhole temperature had been injected at the depth of 1530 m, with ±7 meters interval, known as the upper Frio formation [5]. Figure 5.1 (from [10]) shows the true scale geological model of the Frio injection site.

Time lapse VSP data were acquired in July, 2004 as a baseline and repeated forty five days after the injection in November, 2004 to monitor the injected CO2 [4].

Figure 5.1: True scale model of the injection zone and relevant geological sections.

For recording, three component clamping geophones were operated on a 80 level string which could cover 610 m of the recording depth and for each shot, 1.6 Kg of explosive

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charge were exploded in a shot hole at the depth of 18 m. Totally, eight shot locations were acquired in different azimuth directions. Some other planned shot locations were not operated, due to the permit limitations and flooding. Shot locations are shown in figure 5.2 [5].

Figure 5.2: Eight shot locations for VSP data acquisition.

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6 Data Processing

Globe Claritas V5-6-1, was the main software application for the data processing. The same processing steps were applied to both the post and pre-injection data sets (table 1).

1 Reading Raw Data

2 Sorting Data to Common Shot Gather and Receiver Components 3 Separation of Vertical Components

4 Checking the Quality of Traces and Editing 5 Shot Static Correction

6 Picking the Fist Arrivals Time 7 Wavefield Separation

8 Deconvolution

9 Band Pass Filtering

10 Applying Two Way Traveltime and NMO Correction 11 Converting the Receivers Depth

12 Sorting Data to Common Traces 13 Separation of P and S waves 14 Final Editing

Table 1: VSP Proccessing Steps

These processing steps can be categorized in three major sequences;

1. Pre Processing (steps 1 to 5) 2. Main Processing (steps 6 to 11) 3. Post Processing (steps 12 to 14)

6.1 Pre Processing Sequence

All recording strings had been labeled, individually, by unique shot IDs during data pro- duction. These shot IDs were sorted and aligned for the corresponding shot location to make common shot gathers. Afterward, data were sorted by the component types and the vertical component was separated (figure 6.1).

The final step in this stage was shot static corrections which were applied to the data by using the uphole time shift. The uphole time had been measured by a surface geophone for each string recording (figure 6.2).

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Figure 6.1: Shot gather for source location 1, three components (top), vertical component (below).

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Figure 6.2: Shot gather for source location 1, before (left) and after (right) shot static correction.

6.2 Main Processing Sequence

This phase of processing started with picking the first arrivals time, and by using them, the downgoing waves were flattened to separate the downgoing and upcoming wavefields by median filtering (figure 6.3).

To remove the short-priod multiples, a deconvolution filter was designed on the downgoing wavefield and applied to upcoming waves. Figure 6.4 shows the upcoming waves after deconvolution and band pass filtering with the range of 20-30-100-120 Hz.

Furthermore, Two Way Traveltime (TWT), NMO correction, and corresponding recording depth were applied to the data (figure 6.5).

Figure 6.3: Downgoing (left) and Upcoming (right) wavefileds.

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Figure 6.4: Upcoming waves before (left) and after (right) deconvolution and band pass filtering.

Figure 6.5: Upcoming events for source location 1, after applying TWT and NMO correction.

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6.3 Post Processing Sequence

In this stage, data were sorted to the common traces of the same recording depth in post and pre-injection data sets. Following, the fast median filter was used to remove the effects of S waves and enhancing the seismic traces.

In the final step of processing, the final editing was applied to prepare the data for subtraction and interpretation. Figures 6.6 to 6.11 show the final plots of post and pre-injection for shot locations 1, 2, 3, 4, 6, and 8.

(a) pre-injection (b) post injection

Figure 6.6: Final time-lapse plots of VSP data for shot 1

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(a) pre-injection (b) post injection Figure 6.8: Final time-lapse plots of VSP data for shot 3

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(a) pre-injection (b) post injection Figure 6.10: Final time-lapse plots of VSP data for shot 6

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7 Interpretation

To monitor the injected CO₂, we need to see the differences in time lapse analysis, therefore, pre-injection sections should be subtracted from post injection shot gathers. Com- mon seismic events are expected to be omitted by subtraction and it leads us to see the remaining seismic anomalies in the reservoir due to the changes in the reservoir.

Due to the environmental changes and also random noise, it is not possible to repeat and receive the exact same data in seismic time lapse data productions. To get rid of these undesirable changes, suitable seismic calibration should be applied to the data sets before subtraction.

Hampson-Russell Software provides useful tools for time lapse calibration, comparison, subtraction, and interpretation in the Pro4D⁷ application. The standard flowchart of calibration steps and filters is illustrated in figure 7.1(Taken from Pro4D manual), and some of these techniques were applied on our data sets to monitor the injected CO₂ in the Frio formation.

Figure 7.1: Standard flowchart of calibration steps in Pro4D

7.1 Calibration

After comparing and finding the thresholds for each source location, calibration filters were applied to data sets as follow;

1. Phase and Time Matching 2. Amplitude Normalization 3. Correlation Time Shift

7http://www.cgg.com/default.aspx?cid=852

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In all above filters, pre-injection data have been used as the reference volume to analyze, compare, and apply the required changes to post injection data.

7.2 Subtraction

The next stage after applying the suitable filters and receiving the desire results, is monitoring the differences in time lapse data. The differencing module in Pro4D subtracts input volumes and plots the results. As mentioned, pre-injection data had been used as the reference volume and subtracted from post injection data. The remaining anomalies after subtraction are expected as the reflections of injected CO₂. Figures 7.2, 7.3, 7.4, 7.5, 7.6, and 7.7, show the results of subtracted shot gathers for source locations 1, 2, 3, 4, 6, and 8, respectively.

Figure 7.2: Shot gather for source location 1 after subtraction

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8 Forward Modelling

Producing synthetic seismic models and comparing it with the real data, would be helpful to relate and describe the seismic results with specific targets of the surveys. In this research, forward modeling was done to produce a ray tracing model by using the CREWES⁸ toolbox (traceray − pp) in MATLAB, with the following assumptions:

1. An infinite and horizontal reflector at the depth of 1536 m.

2. Seven layer velocity model was designed by considering the first breaks in the real data (figure 8.1).

3. Vertical receiver profile at the depth of 1201 m to 1533 m with 4 m spacing.

Figure 8.1: Velocity Model

Figure 8.2 shows the ray tracing models for shot locations 1 to 8 and the corresponding traveltime for the assumed reflector for the injected CO₂ at the depth of 1536 m.

In addition, two way traveltime and NMO corrections were applied (with the same cal- culation in real data processing steps), plotted, and merged with the real data plots for further comparisons. Figures 8.3 to 8.7 demonstrate these results for shot locations 1, 2, 4, 6, and 8.

8http://www.crewes.org/ResearchLinks/FreeSoftware/

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Figure 8.2: Ray tracing model and corresponding traveltime

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Figure 8.3: Source location 1 with corresponding TWT from synthetic modeling

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9 Discussion

9.1 Source Locations 1, 2, and 4

Source locations 1, 2, and 4 are the closest shot locations and located in the northeast to northwest azimuth to the injection well (figure 5.2).

The time lapse monitoring shows about 70% changes in reflection amplitudes at the interval of injection depth (figures 7.2, 7.3, and 7.5). Considering the good coverage of synthetic traveltimes (figures 8.3, 8.4, and 8.5), these changes in amplitudes can be interpreted as the corresponding reflections of injected CO₂.

The strong reflection at the depth of 1270 m in the time lapse monitoring of source location 4, could be due to bad geophones, since it is not present in other shot locations (figure 7.5).

9.2 Source Location 3

Source location 3 is around 300 m from the recording well and located in the south azimuth of the injection well (figure 5.2).

Time lapse monitoring in this shot location does not show any anomalies (figure 7.4).

The proper answer to the lack of any changes, is related to the shot location, physical properties of CO₂, and the dip of the layers in the Frio formation. Layers in the Frio formation are dipping around 20 degrees in the south direction (figure 5.1 ), and this caused the upward streaming of injected CO₂ toward the north. Due to the geometry of seismic wave propagation, the shot from a southern source location cannot monitor the injected CO₂.

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9.3 Source Location 6 and 8

Source locations 6 and 8 are located, respectively, at about 350 m in the northeast and about 670 m in the northwest of the injection well (figure 5.2 ).

The same processing sequences for near offset shots have been also applied to these two shot locations, and final results did not show any changes in amplitudes. However, by applying Auto Gain Correction (AGC) with the length of 250 ms and repeating the calibration and time lapse analysis, around 50% changes in reflections amplitude showed up (figures 7.6 and 7.7).

The corresponding synthetic traveltime fits to the results of both shot locations (figures 8.6 and 8.7), but the reflection depth is shallower than nearer offset shot locations.

Probably, it happened due to the shots offset and the layers dip. Rays in these two farther shots, reflected in shallower depth because of the layers dipping, and therefore, cannot record the injected CO₂, close to the injection point. In addition, the 20% difference in observed amplitudes changes (70% in shots 1, 2, & 4 and 50% in shots 6 & 8) can be explained by the same theory; the volume of injected CO₂ decreases by receding from the injection point.

10 Conclusion

The time lapse VSP data from the Frio injection site were processed and interpreted to monitor small scale injected CO₂ (1600 tons) in the top of the Frio formation sandstones at the depth of 1530 m to 1540 m.

Final results from the time lapse processing of three near offset shots (sites 1, 2, and 4) showed 70% changes in reflection amplitudes at the interval depth of injection. The same processing procedure for shot location 3 in the south of the injection well, did not present any differences in the post and pre-injection data sets. In two greater offset shot locations (site 6 and 8), 50% changes in reflection amplitudes showed up at 10 to 20 meters above the injection depth.

Comparing the time lapse results and the synthetic traveltimes led to interpret these amplitudes changing as the results of the seismic reflections due to the injected CO₂ which streams up in the north direction along the sandstones layers dipping to the south in the Frio formation.

Time lapse VSP was successful to monitor the small scale of injected CO₂ and detected the direction of CO₂ flow migration with a good spread geometry of source locations.

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References

[1] Baker and McKenzie, Strategic analysis of the global status of carbon capture and storage - report 1, tech. rep., Global CCS Institute, 2009.

[2] K. Bennaceur, N. Gupta, M. Monea, T. Ramakrishnan, T. Randen, and S. Shinichi, CO2 capture and storage – a solution within, Oilfield Rev, 16 (2004), pp. 44–61.

[3] P. Cook, Carbon dioxide capture and geological storage: research, development and application in australia, International Journal of Environmental Studies, 63 (2006), pp. 731–749.

[4] T. M. Daley, L. R. Myer, G. M. Hoversten, and J. E. Peterson, Borehole seismic monitoring of injected CO₂ at the frio site, GCCC Digital Publication Series, (2005), pp. 1–24.

[5] T. M. Daley, L. R. Myer, J. Peterson, E. Majer, and G. Hoversten, Time-lapse crosswell seismic and vsp monitoring of injected CO₂ in a brine aquifer, Environmental Geology, 54 (2008), pp. 1657–1665.

[6] EIA, International energy outlook, tech. rep., Energy Information Administration, April 2004.

[7] W. Galloway, D. Bebout, W. Fisher, R. Cabrera-Castro, J. Lugo- Rivera, and T. Scott, The Gulf of Mexico Basin, Geological Society of America, 1991.

[8] B. A. Hardage, Handbook Of Geophysical Exploration, vol. 14 of Vertical Seismic Profiling, Pergamon, 1983.

[9] N. Henoch, Processing of vsp data at ketzin CO2 storage site, Master’s thesis, Uppsala University, 2008.

[10] S. D. Hovorka, M. H. Holtz, S. Sakurai, and P. R. Knox, Environmental quality to accompany a class v application for an experimental technology pilot injection well, frio pilot in CO₂ sequestration in brine-bearing sandstones, tech. rep., Texas Commission, 2003.

[11] P. Kennett, R. Ireson, and P. Conn, Vertical seismic profiles: their applications in exploration geophysics, Geophysical Prospecting, 28 (1980), pp. 676–699.

[12] M. W. Lee and A. H. Balch, Computer processing of vertical seismic profile data, Geophysics, 48 (1983), pp. 272–287.

[13] J. L. Mari, F. Glangeaud, and F. Coppens, Traitement du signal pour géologues et géophysiciens, Éditions Technip, Publications de l’Institut fran¸cais du pétrole, 1997.

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[14] B. Metz, O. Davidson, H. de Coninck, M. Loos, and L. Meyer, Carbon dioxide capture and storage, tech. rep., Cambridge University Press, 2005.

[15] J. P. MORTON, Rb-Sr evidence for punctuated illite/smectite diagenesis in the oligocene frio formation, texas gulf coast, Geological Society of America Bulletin, 96 (1985), pp. 114–122.

[16] J. Rakowski, CO2 capture technologies – conclusions for poland, (2006).

[17] E. G. Sanchez, Pleistocene facies in the subsurface of the Southeast Texas Coastal Plain, PhD thesis, The University of Texas at Austin, 1974.

[18] A. A. Tabakov and K. V. Baranov, Integrated land seismic and vsp survey geometries offer improved imaging solution, First Break, 25 (2007), pp. 97–101.

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Time lapse VSP monitoring of small scale injected CO2 in the Frio formation, Texas, USA

Examensarbete vid Institutionen för geovetenskaper ISSN 1650-6553 Nr 275

Ershad Gholamrezaie

Ershad Gholamrezaie

Time Lapse VSP Monitoring of Small scale Injected CO in the Frio Formation, Texas, USA

Time Lapse VSP Monitoring of Small scale Injected CO in the Frio Formation, Texas, USA 2

Examensarbete vid Institutionen för geovetenskaper ISSN 1650-6553 Nr 275

Ershad Gholamrezaie

Time Lapse VSP Monitoring of Small scale Injected CO in the Frio Formation, Texas, USA 2

Supervisor: Christopher Juhlin

Acknowledgement

Contents

List of Figures

List Of Abbreviations

1 Introduction

2 CO

Capture and Storage (CCS)

2.1 CO

Capture

2.2 CO

Transportation

2.3 CO

Storage

3 Vertical Seismic Profiling (VSP)

3.1 Introduction

3.2 The Concept of VSP

3.3 Typical VSP Processing

4 The Frio site background

4.1 Location

4.2 Geology

5 VSP Data Acquisition at the Frio Site

6 Data Processing

1 Reading Raw Data

2 Sorting Data to Common Shot Gather and Receiver Components 3 Separation of Vertical Components

4 Checking the Quality of Traces and Editing 5 Shot Static Correction

6 Picking the Fist Arrivals Time 7 Wavefield Separation

8 Deconvolution

9 Band Pass Filtering

10 Applying Two Way Traveltime and NMO Correction 11 Converting the Receivers Depth

12 Sorting Data to Common Traces 13 Separation of P and S waves 14 Final Editing

6.1 Pre Processing Sequence

6.2 Main Processing Sequence

6.3 Post Processing Sequence

7 Interpretation

7.1 Calibration

7.2 Subtraction

8 Forward Modelling

9 Discussion

9.1 Source Locations 1, 2, and 4

9.2 Source Location 3

9.3 Source Location 6 and 8

10 Conclusion

References

Time Lapse VSP Monitoring of Small scale Injected CO in the Frio Formation, Texas, USA ²

Time Lapse VSP Monitoring of Small scale Injected CO in the Frio Formation, Texas, USA ²