Azimuth-dependent ocean bottom cable receiver coupling to the seafloor

GEOPHYSICS, VOL. 79, NO. 6 (NOVEMBER-DECEMBER 2014); P. P21–P29, 8 FIGS.

DOI: 10.1190/GEO2013-0330.1

Abstract

Inconsistent horizontal receiver coupling to the seafloor causes measured signal differences on both horizontal re- ceiver components. To explain this inconsistency, we con- sidered distinct coupling parameters, the damping ratio and resonance frequency, for the receiver inline and crossline di- rections. Our approach combined these coupling parameters with the azimuth angle between an airgun shot and the re- ceiver geometrically and used two visualization methods to show spatially dependent receiver coupling, based on corre- lation and root-mean-square amplitudes. We developed fi- nite-element method simulation results together with field data from one ocean bottom cable (OBC) in very soft bio- sediment. The simulations provided an insight to the differ- ence between perfectly coupled ideal receiver response and poor coupling. From the field data, we compared OBC re- ceiver coupling for trenched and untrenched cable. Our re- sults revealed that the field data had an azimuth-dependent response pattern with amplitude decay and time shift on the untrenched inline component, which we can reproduce with our simulations. Azimuth-dependent receiver coupling indi- cated that the inline and crossline receiver components were connected by the direction of the traveling wave, and trench- ing the cable will reduce the azimuth-dependent coupling effects.

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Systematic simulation of multicomponent receiver coupling to the seafloor using rheological models

GEOPHYSICS, VOL. 79, NO. 6 (NOVEMBER-DECEMBER 2014); P. P9–P19, 17 FIGS., 4 TABLES.

10.1190/GEO2013-0329.1

Abstract

This paper reports a comparison of three different rheological models used to characterize receiver coupling to the seafloor. We used a finite-element simulation tool to simu- late the mechanical receiver coupling to the seafloor as a viscoelastic system with a combination of linear elastic springs and linear viscous dashpots, known as rheological models. Three models cover most of all mechanic coupling systems, the most commonly applied Kelvin-Voigt model (KVM), the Maxwell model (MM), and the standard linear solid (SLS) model. The models differ in behavior for differ- ent coupling aspects such as oscillation, creeping, stress re- laxation, and their combinations. We tested these models’ ability and relevance for use in modeling seismic receiver coupling to the seafloor. For that purpose, we used an opti- mized mathematical approach to simulate coupling behavior under various coupling conditions. We found how receiver coupling will affect P- and S-waves for all three models and provided some insight into which model is most suitable to describe coupling under different circumstances. We found that the SLS model represents a general description of most of the coupling effects to the seafloor and should be used when the coupling acts as a viscoelastic system. The KVM and MM are applicable in extreme cases, such as for elastic waves in consolidated sediments (KVM) and dominant creeping effects, as in very soft biosediment (MM).

Fourth Passive Seismic Workshop 2013 Amsterdam

I summarize the presentations and talks during the coffee breaks on the EAGE Fourth Passive Seismic Workshop (WS) from the 18.03.2013-20.03.2013. The main focus was on optimizing development of unconventional reservoirs and the program was separated into five sessions with following topics: acquisition, surface monitoring, processing & moment tensor inversion, induced seismicity and surface characterization & interpretation.

Background

Micro-seismic Event Detection (MED) is fast becoming a significant tool for offshore reservoir monitoring. The E&P industry, driven by field operator requirements for real-time data on hydraulic and geomechanical processes, presently needs more information to understand dynamic reservoir changes. MED is an important tool for hydraulic fracture detection, the mapping of reservoir stresses and seismic hazard analysis which are in turn key indicators for evaluating reservoir dynamics and associated environmental risks.

This technique is based on previous observation of very small earthquakes with magnitudes down to Mw = -4 or even lower generated by the production activities in a reservoir.

Micro-seismic events are distributed at specific locations and follow the fault structures in the reservoir. These structures act as flow channels and routes for premature fluid or gas breakthrough in the reservoir, destroying the cap-rock integrity with surface subsidence as result. MED typically identifies such reactivated fault structures with significantly greater accuracy than seismic-surveys. In addition to 4D seismic surveys MED can also be used to provide real-time 3D monitoring of the change in fluid-pressure distribution. Conventional MED approaches use vertical receiver-arrays in injection or production wells facilitating event-detection ranges of approximately 1Km from the well. Studies demonstrating the feasibility of offshore surface receiver for this technique were conducted from 1997 onwards.

Micro-seismic detection relies on the detection and analysis of large numbers of micro-earthquakes using surface receiver arrays to provide detailed information about the effects of hydraulic fracture, stress induced reactivation of faults and changes in pore pressure in the reservoir.

Micro-seismic detection is based on seismology techniques; hence the receiver position is not as important as the sensor-node quantity. Like standard earthquake seismology, the resultant micro-seismic event detection is more accurate the more receivers can be used for measurement with larger distance between each receiver. Short distance receivers will not increase the accuracy of the event location. In order to locate an event it is only important that it is situated within the receiver-array’s geometric boundary. Ray-tracing can help to estimate shadow-zones (caused e.g. by faults/ fractures) and to estimate the velocity model.

Summary

This WS was very inspiring and informative with interesting discussions, good presentations and an overview what is state-of-the-art. MED is a widely accepted industrial tool and is about to become an additional tool for permanent reservoir monitoring. In order to understand the dynamic changes in the reservoir/hydraulic fracture zone more information are needed than provided during a short measurement campaign. MED is also an important factor in hydraulic fracture detection, mapping reservoir stresses and seismic hazard analysis.

There is a common understanding in the WS community that any type of fluid injection will cause microseismic fractures in a reservoir or fracture zone, to what extent is still under discussion. The wave-form inversion calculation of the focal mechanism by the moment tensor can estimate tensile openings and closures. This is an important step to understand what really happens in the reservoir or overburden. The result can “easily” be plotted into a Hudson-diagram which shows the opening and closing of fractures during fluid injections over time.

To do a proper wave-form inversion it is necessary to have accurate velocity-models, estimated rock parameters (e.g. resonance frequency, Q-factor…) and an understanding of the source mechanism. All this parameters are difficult to get, and assumptions have to be made. The focal mechanism and moment tensor inversion was presented and discussed on the WS, but from my point of view nothing new. The same methods are used as presented on the last passive seismic WS and I think the visualization of the moment tensor, like beach-balls are made for scientists rather than engineers. But the engineers have to make their decisions on the results we provide and therefore easier understandable visualization methods should be developed. Some improvements already exist like the use of Hudson-diagrams and fracture volume-plots.

However, microseismic monitoring is an engineering tool and I got the impression that we are losing the reason why we are doing all this. I am still missing the link between fracture volume estimation (if possible) and microseismic events. How can we calculate e.g. the fracture size and orientation? How can we estimate the fracture volume? And how accurate are the results? This are questions to be answered, only to name some.

This WS showed that we have microseismic detection workflows in place to determine the source location and moment tensor as soon as we are able to detect microseismic events. But in order to make microseismic events detectable, we have to add some steps which are not well discussed yet. This steps are not in the main focus, but I think they are equally important than event detection, moment tensor inversion and estimation of the focal mechanism.

The first step should be the a more or less standardized feasibility study, but this will require access to a geophysical model with high accurate velocities models as well as the Q estimation and the receiver characteristics. With some assumptions with respect to the characteristics of microseismic events, we can calculate the attenuation of the event with distance from its location. The measured event Magnitude at the receiver position can be evaluated. Furthermore the signal to noise ratio (SNR) improvement with different number of receivers used can be predicted. The result of this feasibility study will be the evaluation of the maximum achievable detection ranges for different receiver configurations. The feasibility study should also include some synthetic experiments using different microseismic sources of different sizes which are triggered at specific locations along a fracture/fault plane in the model in order to quantify detectability with size, depth and noise level of the source.

There will be not one workflow to fix all requirements, but the useful combination of preprocessing methods will be the key to improve the measured data.

Estimation of OBC coupling to the seafloor using 4C seismic data

SEG Technical Program Expanded Abstracts 2012

DOI 10.1190/segam2012-1066.1

Abstract

The presence of an Ocean Bottom Cable (OBC) in the seabed produces changes in the local wave field due to coupling, usually referred to as wave field distortion. The coupling system response of the sensor sediment interaction can be modeled as a mass spring transfer-function with two coupling parameters: resonance frequency and damping factor. The transfer-function is related to the mass and size of the sensor housing and the physical properties of the sediment. In order to improve the system coupling it is necessary to estimate the coupling parameters to shift the coupling resonance to a higher frequency; and the damping to critical damping. We will show how the coupling parameters (resonance frequency and damping factor) can be used to obtain the sensor housing response by using an “iterative loop” method to estimate the coupling parameters. We will also present two case studies, one in very soft bio sediment in a harbor area and the second in the Gulf of Mexico.

Qualitative seismic sensor array estimation and seafloor coupling by using incoherent ambient signals for reservoir-monitoring systems

SEG Technical Program Expanded Abstracts 2010

DOI 10.1190/1.3513884

Abstract

Seismic sensor array attribute analyses on ocean bottom cables (OBC) are becoming powerful methods for evaluation and calibration of seismic sensors. But reservoir monitoring arrays are counting several 1000 sensor‐nodes and to quality check all sensors in an array is a time consuming and cost intensive procedure. Nevertheless, the reliability of the sensors is crucial and has to be proven prior to each survey. A qualitative estimation of the sensor coupling to the seafloor is a critical factor to improve the pre‐processed data. I will describe a method for Qualitative Seismic Sensor Estimation (QSSE) to estimate the different behavior between sensors in a reservoir monitoring array as well as the sensor coupling to the seafloor. The significant benefit of this method is to get a qualitative statement about the amplitude and phase response over the frequency‐band of interest before a survey starts. The quality control (QC) of seismic data adds contributes significantly to the turnaround time of pre‐processing and takes place after a survey. QSSE provides QC information prior to the survey and helps to fine‐tune the seismic QC attributes or improves the data quality during preprocessing. Conventional QC practices have to handle a large variety of attributes with a priori information like RMS calculations during a survey. Instead of different types of RMS measurements in the time domain QSSE provides the sensor quality and seafloor coupling in the frequency domain in one result. Therefore QSSE extends information about the seafloor coupling comparing two components, neighbors or each sensor with a reference sensor. I shortly present the mathematical description of this method and some case studies to confirm the usability of QSSE. The case studies demonstrate the usefulness of this method and that the turnaround time can be decreased because of a better understanding of the sensor behavior and the sensor coupling to the seafloor. QSSE provides a frequency depending amplitude and phase‐shift plot or a single average value for the frequency‐range of interest.

INOSACS

Iinosacnvestigation and optimization of OBC sensor array coupling to the seafloor

The most important challenge for the oil-industry is to increase the recovery rates for existing fields and to map fluid movements with time-laps 4D seismic, reducing geo-hazard like cap-rock integrity, subsidence or to monitor CO2 storage in an offshore reservoir by using active and passive sources (e.g. Airgun-survey and passive/microseismic). The seismic equipment is configured as sensor lines with cables trenched and covered on the sea-bottom.

The equipment typically comprises up to 4000 sensor nodes depending on the aerial extent of the reservoir. The system will preferably be connected directly to onshore operation centers by means of broadband communication and data can be controlled and processed for QA purposes in real time. Traditional 4D seismic techniques re-shoot a specific reservoir using conventional towed streamer techniques, trying to map and assess changes in the reservoir by having a repeat interval of 2-3 years.

I started in September 2010 a new research project in cooperation with Octio Geophysical AS and the University of Bergen and this project was successfully finished in October 2013.

There will be two main objectives for this project. The first will be a systematic investigation of OBC coupling to the seafloor for a better understanding of the horizontal coupling mechanism to increase the signal quality for 4D seismic, micro/passive seismic and fluid flow in a reservoir by injection of water or super critical CO2.

The second objective is to design a new OBC sensor-housing (node) to improve the coupling and a test on a real reservoir in cooperation with a costumer or in an addition research project.

In order to improve sensor coupling in the offshore environment novel and systematic approaches are needed. Today several approaches exist for the vertical component of a three component sensor. But there are no systematic investigations for the horizontal components. Most of the vertical approaches use special pre-processing methods like separation of upgoing and downgoing P and S wave-fields or inverse filtering.

But to understand the sensor coupling to the seafloor it is essential to investigate the sensor coupling itself. or a systematic investigation it is substantial to understand the connection f different sensor-housing designs to variable seafloors. Which design makes the sensor coupling better and why? What influence has the seafloor oil conditions and how deep should an OBC be trenched and how strong is he cable-tension influence? Why is the sensor coupling different for all three components? All these questions will be investigated by using simulations and doing tests in a water-tank. The water tank will be hanged to the floor to decouple the water-tank from the ambient noise.

The most critical challenges will be to simulate the correct soil coupling with the sensor-housing for horizontal movements, because current models its not into measurements and can only be seen as a start model. To find the optimal mechanical node design is also a critical challenge, because of to integrate the new design into the offshore installation procedures