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The next global standard for hydrocarbon detection and oil field monitoring.



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Marmot Passive Monitoring Technologies SA

c/o H&B Law
Rue des Vignerons 1 B
CH - 1110 Morges VD
Switzerland

www.passive-monitoring.com info@passive-monitoring.com

 Background 

Paul Rode, 2017

Introduction/Abstract
Passive Monitoring Technologies are those that detect and compile ‘background noise’ emissions across a wide span of wavelengths and do no generate a signal themselves. They depend on the cognitive interpretation of all background noise and are, therefore, broadband communication/detection systems. They require very highly sensitive sensoric capability and very advanced signal processing, analysis and interpretation. They are used to detect and monitor, which means they provide information about the localization and the nature of target and its contemporary behavior across time.

1. Background and History of 5DQM Monitoring

Passive Monitoring or passive observation has been known since the beginning of organic life on earth:
The observation and interpretation of dynamic changes in the environment is the pre-condition for successful survival.

In the course of the technical evolution human beings lost many of their “natural senses” or the ability to rely on them. On the other hand they developed numerous technical aids and instruments in order to enhance their senses, such as X-Ray, Radar, Sonar and Reflection Seismic systems and also optical and thermal sensing devices.

Most of such devices are of active nature and were developed for advanced applications for the defense, medical and resource industry.

Active systems apply a technical controlled signal source using the principles of reflection, refraction or reaction at the structure or at the target which is to be observed. The information results of such systems are mostly one dimensional and equivalent in kind to the energy emitted from the source. Therefore, the information results are limited. They are mostly applied to locate objects.

As noted, Passive Monitoring Technologies depend on the cognitive interpretation of any kind of background noise and are broadband communication systems. They use a very highly sensitive sensoric capability and require a very advanced process of signal analysis and interpretation. They are mostly used to detect and provide information about the localization and the nature of an object and its contemporary behavior: Detection means localization and identification. Monitoring provides continuous localization and characterization through time.

The “object” or “the subject of detection” is sometimes defined as a “Technical Dynamic System” (TDS).

The “Information Carrier” which is used by Passive Monitoring Technologies is based on the “Dynamics” of phenomena and it can be of acoustic, electromagnetic, gravity or chemical nature. (In earth dynamics this is a coupled quadruple).

The core element of a passive monitoring system is the “Cognitive Data Management System” (CDMS).

The CDMS is converting Signals into Information
Any CDMS contains a so called Forensic Data Base (FDB) (also called “Event Space”) and its knowledge content can be genetic or/and it has to be learned – which means at the beginning of a measurement cycle the identification capability of the CDMS is limited to the genetic base content of the FDB.

This base genetic content is improved and upgraded by significant experience data – learned – during the measurement cycle

Figure 1Figure 1: Organization of the FDB

by the continuous data stream which is purely generated by the broad spectrum of permanently acquired random noise.

The sole technical purpose of a passive monitoring system is to control a technical dynamic system – the behavior of which is primarily unknown (unless you have already a model but this model is then imbedded in the genetic FDB) with data which are primarily unknown.

The technical dynamic system described may be a producing Oil reservoir or a petrogeothermal heat exchanger. In both cases the acquired information from the CDMS is fed back in a closed feedback control cycle into the operating system and operations of the subject to provide control and optimization.

Figure 2Figure 2: Feedback Loop Control System of a producing Oil Reservoir

In the simplest case a model of the system response already exists in the genetic section of the FDB but most cases the behavior of the system is unknown and the model can only be created from the “learning process” of the CDMS (This means “BIG DATA and “Quantum Computing”).

Therefore the CDMS has a learning curve for its capability of recognition before it can create control data for the system under observation and control. But at the end the CDMS can calculate the entropy of the TDS based on the total content of the Forensic Data Base and then predict the future behavior of the TDS which is the goal and pre-condition for effective system control:
Control of a technical dynamic system requires calculation of the behavior of the system in future, at least in the time span of the time constant of the system response.

Figure 3

Figure 3: Time delay model for system response in a producing oil reservoir.

The best example for such a passive monitoring system equipped with a sensitive broadband sensor array and a cognitive data management system is a good tennis player: In the beginning of the match he knows nothing but he has already his experience about the behavior of systems (FDB) and he has his technical skills and during the course of the match he is building up his FDB and his brain with its optical and acoustic sensors is calculating the entropy of the system – counterpart – bottom – ball – racket – speed.

Marmot has developed a system called “5D Quantum Monitor” (5DQM) for the identification of acoustic dynamic earth phenomena.

Figure 4

Figure 4: 5DQM components based on a synthetic acoustic planar antenna and a Cognitive Data Management System.

The „5D Quantum Monitor“ presents an advanced measurement and control system for the surveillance – control and prediction of fluid and non-fluid subsurface dynamics.

The “5D Quantum Monitor” is based on a broadband seismo-acoustic directional planar antenna system (the SPIDER) and a “Cognitive Data Management System” (CDMS)
based on a Forensic Data Base – Event Space  – and the forward modelling of the behavior of a dynamic system.

The application of this measurement technology is demonstrated in the graph below (Figure 5). There is a large demand worldwide in the following specific categories:

Figure 5

Figure 5: 5DQM Application

Marmot's PointEnhanced Geothermal Systems Control for Optimization of Heat Exchanger performance vs. Induced Seismicity
Marmot's PointEnhanced Oil Recovery for the Control of Fluid Dynamics vs. production efficiency and induced seismicity and subsidence
Marmot's PointMonitoring of artificial underground storages and waste deposits in natural formations
Marmot's PointControl of industrial system integrity
Marmot's PointIntrusion control and defense applications
Marmot's PointMechanistic Acoustic-Seismic Hazard Assessment (MASHA) or earth quake post shock early warning system

Summary and conclusion:

Permanent Passive Monitoring Systems are the basic instruments to control the social economic development  of the human community.

Permanent Monitoring Systems by nature have to be passive and they depend on the capability to handle “BIG DATA” and “Cognitive Data Management Systems” to convert large quantities of non-structured random data into information and a feedback tool.

The front end of a passive monitoring system is a technical receiver array which is always an analog device in the acoustic or electromagnetic domain and the outcome of the system is a control and steering tool for all kind of development processes based on the accumulation of information created by artificial intelligence.

Figure 6

Figure 6: Passive monitoring front end device: Directional Acoustic Planar Antenna Array

Marmot's PointPermanent Passive Monitoring Systems have to be seen as an intelligent survival and control tool for any kind of dynamic systems
Marmot's PointToday essential for the control of political and social economic development but also essential for the control of all kind of production and logistic processes.
Marmot's PointA technical control and steering tool for the efficient exploitation of hydrocarbon reservoirs and all kind of natural resources
Marmot's PointA control tool for heat exchanger performance in Enhanced Geothermal Systems
Marmot's PointEarth Hazard Assessment and warning systems
Marmot's PointEnhanced security systems

2. The 5D Quantum Monitoring Concept and Reservoir Engineering

2.1. State of the Art
There are fundamental ways in which the 5D Quantum Monitoring (5DQM) concept differs from conventional seismic surveys performed in the energy industry.  The 5DQM system makes use of the continuous broad spectrum ‘background’ signal passing through the subsurface of the earth.  The system continuously, passively, and noninvasively monitors the modifications or alterations in the signal form as it passes through the targeted volume; from baseline differences that exist at project initiation to the continuum of differentials that develop through time. Conventional 2D/3D/4D seismic monitoring methods generate a compressional source wave and detect the reflected waveforms and the differentials created in those waveforms at a single point in time.

While both concepts target definition of the reservoir, addressing structural form and the location of different fluids in the reservoir volume, these goals differ in basic nature in each system.
3D/4D Seismic Surveying: Reflection Seismology Defining the Reservoir

Conventional 3D seismic survey methods utilize multiple wave source generators, of various types, to initiate a compressional wave into the subsurface.  These were originally oriented in a ‘line’; a linear array, generating what is now known as 2D surveys, or in multiple linear arrays (two or three) generating a 3D seismic survey.  Reflections of the generated waves occur at formation layer boundaries existing in the subsurface lithology.  These reflections are detected and logged at the surface by geophones/seismic sensors that focus on a narrowly defined range of frequencies.  The character of the reflections are processed and analyzed to infer the depth and character of the formation interface; harder vs. softer rock, and the potential of hydrocarbons existing in a given formation by the damping effect of the fluid saturating the pore space. This is based on the effect of the density of the fluid; water being more dense than oil; gas being much less dense than both.  This is why gas reservoir accumulations can generally be seen more easily, as ‘bright spots’ in generated representations.

The improvement in execution, processing and analysis has made 3D seismic a very useful exploration tool, reducing the risk associated with targeting and developing a given reservoir.  However, as an exploratory tool, it gives only a beginning point of reference for the reservoir.  As a reservoir is produced, fluids migrate, stresses change, and these changes in the subsurface can only be postulated from production/voidage information, coupled with injection volume/location information in a waterflood, and injection and production well endpoint data in fields utilizing ‘smart well sensors’.  A reservoir engineer desires to know what is going on in the 3D black box of the reservoir, as time goes by.  This would allow optimization of operations and enhanced recovery of the resources.

With this in mind, the concept of 4D seismic was introduced and has been embraced, to a significant degree, as a means to determine what changes have occurred in the reservoir at some point in time. This data allows improved history matching of what has occurred and prediction of what will or can occur in the future utilizing reservoir simulators and geo-models. Predictions can be made using existing or modified operational parameters to enhance production optimization and ultimate recovery. However, 4D seismic remains constrained by the fact that it can provide only one, or  more, snapshots in time and does not provide real time monitoring of changes that would allow continuous mapping of reservoir dynamics.  The 4D seismic signal also remains a reflection signal subject to degradation and high signal to noise ratios within the specific dynamic range of the geophones.

2.2. 5DQM Reservoir Description and Monitoring
As previously noted, the 5DQM concept surveys and passively monitors the broad spectrum background radiation signals passing through the subsurface, not technical induced and reflected wave pulses.

Technically the recorded signals cover the converted – from background noise converted and induced signals.

Theoretically the continuous broadband recording process and the forensic data base (FDB) allows for a Bayesian approach for dynamic probability calculation which is fundamentally different from parametric reservoir modelling based on discrete data sets.
There is no issue of attenuation of this complex signal.  There is merely the passage of the complex wave, over a wide range of frequencies, through the subsurface and to surface or near surface detectors, regardless of whether they are being monitored or not.  This signal, however, passes through the layers of the subsurface and any fluids that might reside within specific strata. Both solid and fluid act as spectral filters for the signal, modifying its’ character in a manner that can be detected, analyzed and processed to determine the structure and contents of a three dimensional space.

An easy way to understand the difference is to think of the process of submarine detection.  Everyone is familiar with the concept of sonar which, like reflected seismic surveys, consists of a pulsed wave and the process of receiving the reflected signals of multiple pulses to detect and determine position and movement.  There is a range limit, due to attenuation of the pulse and the reflection, and the accuracy of location determination is dependent on the multiple positions and the relative positions of source and target. It is a means of locating something relatively close by at a given point in time.  However, submarine detection capabilities go far beyond sonar, with permanent arrays set on the ocean floor that continuously receive and process the background subsea wave emanations from many locations.  With data over extended time and signal processing targeting particular deformations/alterations to the background signal, the position and movement of a submarine at distances far greater than the limits of sonar detection can be mapped.  This is akin to what astronomers do in mapping and searching the galaxies.  They look for anomalies that can be identified, tracked and activity inferred by the forensic analysis of the background radiation emanations over time.  They don’t necessarily know what they are looking for, except for deltas at certain frequencies which they can analyze.

Additional and fundamental differences exist.  The sensor array (Figure 6) is not arranged in linear arrays, but in areal patterns in which the detection foci of the individual sensors overlap each other and the array receiver characteristic is directional – arbitrary and controlled DOA.

This type of arrangement has been used employed utilizing standard geophones. However, combined with the lack of sensitivity and discrimination in the frequency ranges that correspond to the subsurface parameters of interest, these applications have been shown to be of little benefit. The background signal strength is lower and the wave pattern far more complex than the induced reflection seismic signal and requires far more sensitive sensors with a more complex configuration.  Greater sensitivity alone, with the low energy signal, results in overwhelming noise and the inability to discriminate signal for analysis. Therefore, in order to implement the 5DQM concept, the development of a uniquely capable sensor was required for signal detection and conversion.  The Marmot signal converter is not only 1,000 times more sensitive than standard or marginally enhanced geophones, but includes key componentry, including multipole noise cancellation circuitry, that provide for discrimination of the signal components for the analysis over specific frequency ranges corresponding to individual parameters of interest. Of note, this converter is much more massive than a typical geophone, which is also required to ensure actual detection and discrimination across signal frequencies.

The signal is continuously monitored.  Analysis is not based on a single signal generation episode in time, as with 3D seismic surveys, nor on two or more isolated signals across time, as in 4D survey analyses. With the advance of computing capabilities and the development of powerful mathematical algorithms – cognitive data management and Bayesian system probability calculation -, the continuous signal data is processed to identify and locate specific parameters within the 3D volume targeted.  Continuous data acquisition and proprietary processing provides for forensic re-analysis of earlier data as time moves forward, contributing to improved parametric and positional accuracy with time.  Entropic predictions are made at the same time. This technology can provide the continuous far field information currently lacking in reservoir analysis and management wherein only limited point source data is available from smart well locations.  Mapping the movement of fluids, as well as structural changes within the reservoir, provides for reservoir management on a previously unavailable level.  When brought into the framework of a 3D geomodel  and compositional reservoir simulator and fully coupled with it, these tools can provide the capability of optimizing reservoir performance by optimizing production, injection and the movement of fluids through the reservoir.

While 5DQM is herein focused on conventional reservoir management application to oil and gas reservoirs, the technology has similar and related value in related applications. The ability to map and monitor both fluid and structural differentials has critical application in scenarios where structural degradation of the reservoir needs to be managed to ensure operational integrity, and the integrity of the surface above,

Figure 7Figure 7: Information flow systematic

such as with the Groningen Gas Field in The Netherlands.  Insufficiently managed water injection has not stabilized the reservoir structure and continued operations are in jeopardy. The ability to map fluid movement and associated structural changes provides a tool in which future water injection may be controlled more efficiently to stabilize and forestall any further structural collapse.  Additionally, the ability to map steam and water movement 3-dimensionally within geothermal systems will also provide for more efficient management and optimization of utilization of those resources.

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