Abstract:
A system and method monitor a hydrocarbon reservoir for drainage in volumetric three dimensions. Monitoring between wells is imperative for optimum reservoir management and is achieved by mapping the hydrocarbon fluid pathways in a producing reservoir. Unlike conventional 4D or time-lapse reflection seismic imaging systems that use a controlled active seismic source and records reflected seismic energy at receivers, the system and method exploit the minute vibrations, or micro-earthquakes generated in the reservoir layers that are induced by fluid movement. These microseisms are detected as the fluids move in the reservoir.

Description:
FIELD OF THE INVENTION 
     The present invention relates to continuous monitoring of fluid paths in a hydrocarbon reservoir by application of passive microseismic emissions. 
     BACKGROUND OF THE INVENTION 
     Microseisms are induced in the reservoir rock matrix due to pore pressure perturbation and geomechanical stress field relaxation as the reservoir fluids are produced and injected. The micro-earthquakes are generated because the stress field in the reservoir is anisotropic. As the in situ stresses are perturbed by reservoir production and injection activities, the resulting changes in fluid pressure create elastic failure in the rocks and cause microseismic events that are detected with special seismic sensors. 
     Microseisms, emanated from the reservoir, with local magnitude (M L ) down to a Richter value &lt;−1 or even lower, are detected. Events below magnitude −3 are often classified as background noise. These microseisms are detected in multi-component seismic sensors with wide bandwith, over distances of 1 km. and more. Conventionally the assessment of changes in the reservoir characteristics over the production time or reservoir fluid flow monitering is achieved with measurements that were in selected wells with down hole instruments only at selected production time intervals. 
     The Richter local magnitude M L  and seismic moment M 0  are computed using the formula: 
                     M   L     =         Log   10     ⁡     (       M   0     -   16     )       1.5             (   1   )               
where the seismic moment M 0  is computed using the formula from Lee, W. H. K. &amp; Stewart, S. W., Advances in Geophysics, Supp. 2, Principles and Applications of Microearthquake Networks, (Academic Press, 1981):
 
                     M   0     =       4   ⁢           ⁢   π   ⁢           ⁢   ρ   ⁢           ⁢     V   S   3     ⁢     W   0     ⁢   R     .85             (   2   )               
R is the source-receiver distance, W 0  is a vorticity parameter, 0.85 is the assumed radiation coefficient, ρ is the bulk density of rocks, and V s  is the shear wave velocity.
 
     The present invention offers a complementary and, in the presence of suitable reservoir rock and fluid properties, an alternative tool for monitoring hydrocarbon reservoirs with time-lapse seismic using-permanent sensors, disclosed in U.S. Pat. No. 5,946,271 to Dragoset. Such inter-well monitoring is also known as four dimensional or 4D seismic that is applied for monitoring the water sweep in a reservoir, disclosed in U.S. Pat. No. 6,886,632 to Raghuraman et al. 
     As water replaces the hydrocarbon fluids in some reservoirs, the resulting saturation change, generates only very small alterations in compressibility and hence in the seismic acoustic properties. This is especially true in hydrocarbon reservoirs with stiff carbonate rock matrix and low compressibility fluids like oil and water. Most of the giant oil fields in the Middle East with carbonate reservoirs have such characteristics. As a result, conventional technique like 4D seismic has only marginal utility in monitoring water sweep in these reservoir settings. 
     Results from recent modeling studies of Arab-D reservoir in the super-giant Ghawar oil field of Saudi Arabia suggest that only small changes in the acoustic properties occur with changes in pore fluid saturation. The reservoir pore saturation changes in the reservoir are due the injected water replacing the extracted oil. The sensitivity of the resulting change in seismic signature in carbonate reservoirs like Arab-D, is extremely low and is often below the detectability of 4D seismic measurements, as described in Dasgupta, S., “When 4D Seismic is Not Applicable: Alternative Monitoring Scenarios for the Arab-D Reservoir in the Ghawar Field”, Geophysical Prospecting, Vol. 53, pp. 215-227, 2005. 
     The application of microseismic technique, however, would be unlikely to detect reservoir pore saturation changes as oil is swept by injected water. It would instead shed light on the fluid pathways. Information on fluid encroachment paths would allow for detection of premature water breakthroughs in production wells; i.e., an early warning system. 
     Accurate monitoring of fluid pathways and delineating the reservoir fluid flow anisotropy optimizes the reservoir management and improves the recovery of oil from these reservoirs. These advantages could be achieved by application of microseismic emissions for detecting anomalous sweep behavior. Such monitoring would also provide an opportunity for remedial design and for optimizing the planning of production and injection well locations for field development. Accurate monitoring also increases the accuracy of reservoir simulation models. 
     Uniform hydrocarbon reservoir fluid fronts and drainage are rare in active fields in production operations. Reservoir characteristics and drainage patterns in most fields are often proven to be much more complex than is initially assumed and are further complicated as the production field matures. The fluid flow anisotropy is related to the heterogeneity in reservoir rocks. The existence of joints, bedding planes, faults, and fractures are common in the sedimentary rock matrix. In most reservoirs, the in-situ stress conditions due to overburden pressure keep these features closed to fluid flow. During the producing life of a hydrocarbon reservoir, physical changes such as fluid pressures result in perturbation in the in-situ stresses. 
     The reservoir stress-field is designed by a conjugate set of axes defined as principal stresses, with σ 1  being the maximum stress, σ 3  being the minimum stress, and σ 2  being the intermediate stress. The stress axes are mutually orthogonal to each other. In order for rock deformation to take place, the principal stress in one direction σ 1  must exceed the other two principal stresses σ 2  and σ 3 . Along the zones of weakness in reservoir rocks, failure occurs that is defined by the known Mohr-Coulomb failure criterion. The increase in differential stress between the maximum and minimum stresses, or a net decrease in the effective normal stress due to the difference between normal stress and pore pressure, causes slippages or rock failure, as described in Marsden, J. E. &amp; Hughes, T. J. R., Mathematical Foundations of Elasticity, Dover Publications, New York, 1994. 
     The following equation defines the Mohr-Coulomb rock failure:
 
τ f =τ 0 +σtan φ  (3)
 
where τ 0 =equilibrium stress state, τ f =shear stress at failure, σ=applied resultant stress, and φ=angle of internal friction.
 
     Such failure or shear-slippage induces microseismic activities and is caused by stress changes in reservoirs with perturbation caused by injection and production. Rock failure can be graphically visualized to occur as the differential stress is increased and the Mohr circle intersects the failure envelope. This occurs due to increase in maximum principal stress or a decrease in minimum principal stress. 
     Reservoir pore pressure change is a major factor in in-situ stress alteration resulting in Mohr-Coulomb failure. Effective stress alteration occurs due to pore pressure changes. Increase in pore pressure due to water injection reduce the effective strength of fractures, joints and faults below the critical shear stress, causing rock failure and thus trigger microseisms. Similarly, oil production from permeable rocks reduces the pore pressure relative to the surrounding lower permeable rocks. This causes a pore pressure gradient and local stress concentrations. Poroelastic changes due to oil production from an Arab-D reservoir concentrates the shear stresses near the reservoir edges or the water flood front. Microseismic events are expected to be concentrated above and below the reservoir. 
     As the reservoir stress is perturbed by fluid injection, shear slippage or rock failure occurs along the zones of weakness like fractures and faults. The shear slippage in rocks generates microseismic activity. These microseisms are detected and their source or hypocenters are located using broad bandwidth borehole sensors. For each microseismic event, it is first necessary to determine the fault plane and slip direction (i.e., the source mechanism) before investigating the source parameters. 
     This analysis is more difficult when only one observation well is available. If several sensors are emplaced in multiple wells and sensors that are widely distributed in space are available, generalized triangulation techniques can resolve the microseismic source locations with high accuracy. The distribution of the sensors relative to the microseismic event source location in the reservoir volume determines the efficiency of the sensor network. Optimum network design of sensor locations is derived by forward modeling and using elastic wave velocities and geomechanical properties of rock formations in the study area. The first arrival times of recorded compressional waves (P-waves) and shear waves (S-waves) and the velocities of the rock layers are used to compute source. location or hypocenter microseisms where the rock failure occurred. 
     Drilling multiple wells for microseismic, however, can prove uneconomical, especially for deeper reservoirs, for which the cost of drilling multiple observation wells becomes prohibitive. Instead of drilling several observation wells for detecting microseisms, in the current invention, the network design consists of a large number of multi-component sensors spatially distributed on the ground surface and cemented permanently in the vicinity of a well. In addition, multi-component sensors are cemented or clamped inside the well bore or borehole at multiple levels in a single well. Such a network provides the capability of detecting a large number of microseismic signals over a wide 3D aperture. The increased density of distributed measurements with respect to the microseismic events in the reservoir ensures that their source points or hypocenters are located accurately. 
     The method for locating the microseismic source has been disclosed in U.S. Pat. No. 6,049,508 to Deflandre, and U.S. Pat. No. 6,920,083 to Therond et al. Such source location techniques are implemented by identifying and classifying the first arrival time breaks and measuring arrival times of P-wave (or compressional wave) and S-wave (or shear wave). 
     Recorded microseismic waves consist of records of P-wave and S-wave. The amplitudes of these P-waves and S-waves are detected and the seismograms are recorded. 
     Also, polarization analysis is performed with hodograms or terminus of a moving vector for particle motion of the waves recorded in the three component (3C) sensors which are oriented orthogonally in the sensor package. The polarization analysis consists in measuring the spatial distribution of a 3C (right-normal basis) signal over a time window using the covariance matrix. Most of the time, the results used are the “azimuth” and the dip inclination of the distribution main direction which is defined by a vector. This analysis determines the direction of a wave&#39;s approach to the 3C sensors or detectors that are planted precisely with a known orientation. With these information and the seismic wave propagation velocities in the reservoir and overburden rocks, the distances between the sensors and the microseismic source in the reservoir are computed. 
     The particle motion of the P-wave defines the direction of the microseismic source from the observation point at each sensor. The plurality of three component sensors in the borehole and spatially distributed over a network on the ground surface provides a redundancy of observations for the same microseismic source. Such a network provides a mechanism for accurate determination of their location. Microseismic events can be located in space and their distribution patterns interpreted in terms of fluid conduction paths, sealing faults or homogeneous sweep. This information will provide improved reservoir management and will allow better planning for future wells. 
     The analysis of recorded P-wave and S-wave amplitude data from the three component sensors provides orientation and direction of the shear slippage in the reservoir as production and injection activities continues. The ratio of the measured S-wave amplitude and P-wave amplitude (S/P ratio) is computed at the microseismic source location. The detected S/P amplitude ratios are compared with predicted values based on geomechanical failure model and their spatial distribution matched using forward modeling. The data determine the rock failure mechanism and their orientation. Reservoir fluids advance preferentially in directions defined by the orientation and distribution of these failure surfaces. Consequently, the failure surface defines the pathways for preferential fluid movement in the reservoir. 
     From the Lee, W. H. K. &amp; Stewart, S. W., Advances in Geophysics, Supp. 2, Principles and Applications of Microearthquake Networks, (Academic Press, 1981); and also Raymer, D. et al., “Genetic Algorithm Design of Microseismic Injection-Monitoring Networks in the Tengiz Field”, SEG Technical Program Expanded Abstracts, 2000, pp. 562-565; the travel time for induced microseismic events from source to receiver involves solving a set of first-order differential equations. A network of sensors distributed spatially on the surface and at different levels in a borehole records a number of arrival times n, for P-waves and S-waves from a microseismic event with hypocenter parameters (x, y, z, t). In matrix notation, the problem of solving the following set of linear equations of condition:
 
AX=B  (4)
 
where A is the n×4 design matrix of partial differentials, X is a vector of four unknown hypocenter parameters (x, y, z, t) and B represents vector differences between the calculated and observed travel times arrival. The design matrix determines the efficiency of the network. For a given matrix A and a set of observations of B, the equation will solve for unknown vector X. The partial differentials define how much the hypocenter parameters will change with respect to travel times. The uncertainty will be large when small changes in travel time cause large changes in hypocenter. This provides a quantitative measure for network performance in locating a microseismic event source.
 
     Performance of the network is evaluated by populating the reservoir volume of interest with trial locations. On this volume, 3D seismic ray trace modeling is performed between the trial locations and the designated sensor positions to produce a complete set of partial differentials. Each partial differential forms a line of the design matrix. The optimal combination of sensor locations in the network is found by solving these equations. 
     SUMMARY OF THE INVENTION 
     The present invention relates to an improved system and method of reservoir monitoring of hydrocarbon reservoir drainage in volumetric three dimensions. Monitoring between wells is imperative for optimum reservoir management and is achieved by mapping the hydrocarbon fluid pathways in a producing reservoir. Unlike conventional 4D or time-lapse reflection seismic imaging system that uses a controlled active seismic source and records reflected seismic energy at receivers, this novel system and method exploit the minute vibrations, or micro-earthquakes generated in the reservoir layers that are induced by fluid movement. These microseisms are detected as the fluids move in the reservoir. 
     A plurality of permanently cemented multi-component seismic sensors deployed spatially on the ground surface and in a borehole are used to continuously record passive micro-earthquakes or microseismic events as the fluids are produced and injected. These events are like earthquakes that result from elastic rock failure of reservoir matrix. The micro-earthquakes are caused due to shear stress release along zones of weakness in rocks. The stress release is due to perturbation caused by reservoir production and injection operations. The injection operations generate increased reservoir pore pressure which causes an increase in shear stress, affecting the stability along the planes of weakness present in reservoir rocks like joints, bedding planes, faults and fractures. Similarly, reservoir production operation or fluid withdrawal creates a pore pressure sink which also affects the stability in the zones of weakness. Seismic elastic waves from elastic failure of rocks in reservoirs are emitted at much higher frequencies than those from large earthquakes. The seismic waves from microseismic events are transmitted from the source location (or hypocenters) to remote sensors (or seismometers). 
     The microseisms or minute earthquakes emanating from the reservoir are detected simultaneously at a large number of multi-component seismic sensors that are deployed permanently at various levels in the borehole and over a surface area surrounding the borehole. Geophones capable of measuring artifact-free frequency response over a 10 Hz to 500 Hz frequency range are used. Physical coupling of the sensors to the formation and the accuracy of the instruments in responding to three-component ground-particle motion are critical. The seismograms recorded in the distribution sensors are all synchronized precisely in time with a Global Positioning System (GPS) clock. Computed source parameters from the microseismic emissions recorded continuously over the production-time can delineate reservoir fluid movements, injection water pathways, and water fingering. Such improved assessment of reservoir dynamic characteristics permit optimized hydrocarbon production strategies. 
     Accordingly, the present invention provides a system for the monitoring of hydrocarbon reservoir drainage fluids in a reservoir dimensions, with the system having a plurality of seismic sensors for detecting microseismic events as the drainage fluids are produced in the reservoir, and for generating corresponding microseismic data; and a computer for recording and processing the microseismic data, and for applying a predetermined data analysis program for determining and outputting a mapping of failure surfaces which define pathways for preferential fluid movement in the reservoir. 
     The plurality of seismic sensors includes: a three-dimensional spatial network having a plurality of surface 3-component seismic sensors permanently cemented below the ground surface; and a plurality of well bore 3-component seismic sensors installed permanently at various levels in a well bore to the reservoir. The microseismic events are detected simultaneously in a time synchronous mode for all of the plurality of sensors using a high precision GPS clock time measurement system. A fluid injection system performs controlled stimulation of the reservoir by cyclical injection of fluids in predetermined start-stop cycles during a calibration procedure for the plurality of seismic sensors. 
     The microseismic events include microseisms, being mini-earthquakes associated with the flow of the drainage fluids in the reservoir, and the computer processes the microseismic data for determining the locations of the sources of the microseisms associated with the detected microseismic events. The computer compares the detected pathways for preferential fluid movement in the reservoir with predetermined computational models of the pathways. The computer also performs microseismic event detection of compressional P-waves and shear S-waves, determines a delay time for the first arrival of the P-waves and S-waves, and determines a polarization of the P-waves and S-waves for determining the azimuthal direction thereof. 
     The computer can also include tomographic analysis means for generating tomograms using the velocity of the P-waves and S-waves for determining the range of the P-waves and S-waves and for imaging the resulting source locations of all detected microseismic events. The computer maps the fluid pathways for reservoir flow anisotropy over reservoir production time from the images of the source locations. 
     In addition, the present invention includes a method for the monitoring of hydrocarbon reservoir drainage fluids in a reservoir, with the method including the steps of: detecting microseismic events using a plurality of seismic sensors as the drainage fluids are produced in the reservoir; generating microseismic data corresponding to the detected microseismic events; recording the microseismic data using a computer; processing the microseismic data using the computer to apply a predetermined data analysis program; determining a mapping of failure surfaces which define pathways for preferential fluid movement in the reservoir; and outputting the mapping through an output device. 
     The method uses the plurality of seismic sensors which include a three-dimensional spatial network having: a plurality of surface 3-component seismic sensors permanently cemented below the ground surface; and a plurality of well bore 3-component seismic sensors installed permanently at various levels in a well bore to the reservoir. 
     The step of detecting includes the step of detecting the microseismic events simultaneously in a time synchronous mode for all of the plurality of sensors using a high precision GPS clock time measurement system. 
     The method also includes the steps of: performing controlled stimulation of the reservoir using a fluid injection system to cyclical inject the fluids in predetermined start-stop cycles; and calibrating the plurality of seismic sensors using the controlled stimulation of the reservoir. 
     The microseismic events include microseisms, being mini-earthquakes associated with the flow of the drainage fluids in the reservoir, and the method processes processing the microseismic data for determining the locations of the sources of the microseisms associated with the detected microseismic events. 
     The method also includes the steps of comparing the detected pathways for preferential fluid movement in the reservoir with predetermined computational models of the pathways, and can further include the steps of performing microseismic event detection of compressional P-waves and shear S-waves; determining a delay time for the first arrival of the P-waves and S-waves; and determining a polarization of the P-waves and S-waves for determining the azimuthal direction thereof. 
     Tomographic analysis can also be performed by the method for generating tomograms using the velocity of the P-waves and S-waves; determining the range of the P-waves and S-waves; and imaging the resulting source locations of all detected microseismic events. The method can also include mapping the fluid pathways for reservoir flow anisotropy over reservoir production time from the images of the source locations. 
     A method is also included for continuous monitoring of fluid paths in a hydrocarbon reservoir, including the steps of: inducing microseisms in the environment of the reservoir; detecting the microseisms using surface seismic sensors to generate surface seismic measurements; detecting the microseisms using borehole seismic sensors to generate borehole seismic measurements; comparing the surface and borehole seismic measurements to locate the microseisms; and mapping the fluid paths in the hydrocarbon reservoir from the located microseisms. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The accompanying figures form a part of the specifications of this novel system and method. These figures illustrate several features of the invention and, along with their descriptions, explain the salient features of the present invention. The same element numbers are used for the same or similar elements in the drawings. 
         FIG. 1  is a schematic illustration of a system and method for detecting microseisms and for determining their source points in accordance with the present invention; 
         FIG. 2  is a schematic cross-sectional view of the system for performing calibration of the microseismic network; 
         FIG. 3  is a schematic illustration of microseismic sensor installations in a borehole; 
         FIG. 3A  is an enlarged schematic illustration of a borehole geophone shown in  FIG. 3 ; 
         FIG. 3B  is a schematic cross-sectional view of the geophone along lines  3 B- 3 B in  FIG. 3A ; 
         FIG. 4  is a schematic illustration of a network configuration of microseismic sensor installations buried below the ground surface; 
         FIG. 5  is a schematic illustration of the microseismic instruments utilized in the present invention; 
         FIG. 6  is a schematic illustration of surface facilities utilized in the present invention; 
         FIG. 7  is a schematic illustration of the system in operation with a reservoir; 
         FIG. 8  is a cross-sectional view of the system of the present invention in operation; 
         FIG. 8A  is a schematic illustration of the Mohr-Coulomb rock failure criterion under triaxial differential stress; 
         FIG. 9A  is a schematic illustration of shear slippage along existing weak zones like faults, fractures and joints; 
         FIG. 9B  is a mapping of faults determined from microseismic hypocenters using the present invention; 
         FIG. 10A  is a schematic illustration of data from a surface sensor in the field; 
         FIG. 10B  is a schematic illustration of data from a down-hole sensor in the field; 
         FIG. 10C  is a graphic representation of data of reservoir characteristics; 
         FIG. 10D  is a schematic illustration of data processing of the x-components and y-components of seismic data to plot two-dimensional hodograms of the seismic data; 
         FIG. 11  is a schematic illustration of processing flow for microseismic data recorded on the surface and in levels in a borehole; 
         FIG. 12  is a graphic representation of the seismic data of shear slippage of reservoir rocks; 
         FIG. 13  is a schematic illustrating the shear slippages of reservoir rocks; and 
         FIG. 14  is a schematic illustrating the components of a data processing computer used in the present invention. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     As shown in  FIGS. 1-14 , the present invention advantageously provides a system and method for continuously detecting passive microseismic events or micro-earthquakes for monitoring fluid pathways in a hydrocarbon reservoir. Anisotropic fluid flow or uneven directional flow rate is commonly associated with reservoir production and injection operations. As fluids are produced from, and injected into the reservoir, microseismic events are generated due to the flow anisotropy. 
       FIG. 1  is a schematic representation of a system  10  using the methods described herein for detecting microseisms and for determining their source points that are related to the shear slippage along zones  16  of weakness in reservoir rocks  34  of a reservoir  14 . Microseismic signals emanate from the zones  16  as fluid injection and production activities cause perturbations in the reservoir  14 . According to this invention, 3-component seismic sensors  18 ,  20  are deployed below the surface  22  and in a well bore or borehole  11  by cementing or clamping them permanently in a well  12 .  FIG. 1  illustrates a preferred embodiment of the instrument configuration for such a system  10 . The microseismic event emissions  55  are detected by the sensors  18 ,  20  in the entire system  10 . The emissions  55  are transmitted in spherical waves from the source location  24  as shown, which could be approximated by rays of the microseismic event emissions  55 . The sensor data from the sensors  18 ,  20  are collected in a central unit  60  and transferred through a communications medium, such as a high speed wireless local area network employing, for example, commercially available “WIFI” devices  61  licensed by the “WIFI” Alliance. The transferred sensor data are received and recorded in a seismic server  62  for processing and for storage, for example, in a data or disk storage device  65 . 
     The reservoir  14  with oil  30  and water  31  is idealized to be composed of a large number of small equal-size cubes. These cubes or grid blocks either contain location of shear slippage  16  with resulting microseismic activity or with no activity. When contiguous grid blocks contain microseismic events emanated from within, they are likely to be due to a system of fractures that have been temporarily or permanently displaced by the fluid flow from water injection or oil production. These cells with microseismic activities would therefore be interconnected to hydraulic flow and would constitute fluid flow pathways along these preferential directions. Grid blocks having no microseismic activity are the zones with no preferential fluid flow directions or isotropic flow. By continuously interrogating all the cells in the reservoir volume for microseismic activities in the sensors  18 ,  20  in the borehole  11  and those on the ground surface  22 , the system  10  and method of operation can empirically determine an estimate of the flow anisotropy and fluid permeability. The network of microseismic events detected throughout the reservoir  14  using the system would form a conductivity network. 
       FIG. 2  schematic cross-sectional view of the system  10  for calibration of the microseismic network. The surface 3-component sensors  18  and borehole sensors  20  detect the microseismic waves as water is injected in an injection well  26  to create an injection pulse test induced source  33  of microseisms. The well  12  is drilled and instrumented with the sensors  20 , and operates to perform both monitoring and production. A controlled injection program or injection pulse test is conducted by start-and-stop injection. As pressure is increased the resulting microseismic events  44  are detected in the sensor network composed of all of the sensors  18 ,  20 . After network calibration, the routine injection and production continues, and so the perturbations due to these activities cause elastic failure in reservoir rocks along shear zones  16  of weakness and cause microseismic events  35 . 
       FIGS. 3 ,  3 A, and  3 B illustrate a design of microseismic sensor installations in a borehole  11 . The 3-component borehole sensors  20  include geophones  28  which are clamped to a tube  29  extending down into the borehole and permanently cemented in the well  12 . 
       FIG. 4  illustrates a network configuration  32  of microseismic sensor installations of ground-based sensors  18  buried below the ground surface  22 . The sensors  18  are cemented, for example, in fifteen feet deep holes and are cemented with grout and bentonite mud. The connectors  38  from the sensors  18 ,  20  can be cables buried, for example, in two feet deep linear trenches. The surface sensors  18  can be on the surface and/or can be buried in relatively shallow depths near the surface  22 , and the surface sensors  18  can be distributed analog-to-digital (A/D) detectors and recording devices. The surface sensors  18  and borehole sensors  20  are connected by the connectors  38  to a Worldwide Interoperability for Microwave Access (WIMAX) compatible communication system  40  using “WIFI” compatible devices. 
       FIG. 5  is schematic of the microseismic instruments of the system  10  shown in greater detail. The central unit  60  can include a pre-amplifier  66 , an A/D converter module  68 , a multi-channel data acquisition unit  70 , and a GPS receiver and clock device  72 . The microseismic signals detected by the surface sensors  18  and borehole sensors  20  are amplified by the pre-amplifier  66 , and digitized in the A/D converter module  68 . The digital data are recorded in the multi-channel data acquisition unit  70  that also records the GPS time measured by the GPS device  72  and synchronized for all of the sensors  18 ,  20 . Each seismic trace record includes a time stamp encoded on the data to identify the time of occurrence. 
     The seismic trace records, timestamped and in digital form, are transmitted by “WIFI” compatible devices  61  to the seismic server  62 , which can include a microseismic event processing device  74  as well as a seismic processing system  76  for applying, for example, data analysis software and signal processing techniques, as described herein. 
       FIG. 6  represents a schematic of the surface facilities in the preferred embodiment. The surface sensors  18  and the borehole sensors  20  are networked by the connectors  38  to a central electronics system  78  that is connected to the WIMAX wireless communication system  40  using “WIFI” devices. The data are transmitted by a WIMAX antenna  80  to a central office computer of the central unit  60 , and also connected to a site office  82  at the well location for data quality checks. 
       FIG. 7  illustrates operation of the system  10  during the production life of a reservoir  14 , in which shear slippage along failure surfaces occur at various times. The borehole sensors  20  are deployed in a production well  12  during operation and production of oil. The microseismic events  44  generate emissions  55  which are detected continuously in the 3-component sensors  18 ,  20  on the surface  22  and in the borehole  11 , and which are processed by an instrument cabin of the central unit  60  for transmitting the amplified and digitized microseismic data by WIMAX communications via the antenna  80 , as described in connection with  FIG. 6 . 
       FIG. 8  illustrates an alternative embodiment of operation of the system  10 , in which the borehole sensors  20  are deployed in a dedicated monitor well  84 , which can be drilled solely for monitoring, or which can be an abandoned well which is no longer used for production. With all sensors  18 ,  20  installed on the surface  22  and in the monitor well  84  drilled for the purpose of monitoring, microseismic events  44  are induced to calibrate or test the microseismicity in the reservoir  14  by pulsing the injection well  26  with cyclically applied water. In long term monitoring, microseismicity induced by fluid movements are continuously recorded in the sensor network of sensors  18 ,  20 . 
       FIG. 8A  illustrates the Mohr-Coulomb rock failure criterion under triaxial differential stress. This criterion explains the source of induced microseismicity in reservoir rocks caused by stress variation due to injection and production activities. To visualize stresses on all the possible planes, a graph called the Mohr circle  86  is drawn by plotting normal stress vs. shear stress. The graph  88  defines principal stresses that will produce this combination of shear and normal stress, and the angle  90  of the plane in which this will occur. The diameter  92  of the Mohr circle  86  defines the differential normal stress between maximum and minimum stress. The strength increases linearly with increasing normal stress. The straight line  94  defines a strength/failure envelope. The angle  90  which the straight line  94  makes is the angle of internal friction or the cohesive strength of the rock matrix. When the Mohr circle  86  gets larger due to large differential stress, the Mohr circle  86  intersects the straight line  94  and induces a rock failure and associated microseisms. 
     The intersections of the Mohr circle  86  with the normal stress axis are σ 1  and σ 3 , which are the maximum principal stress and the minimum principle stress, respectively. The intersection of the straight line  94  with the shear stress axis is τ 0  which is the equilibrium stress state. The area above the straight line  94  is a zone of instability, and the area below the straight line  94  is a zone of stability. 
       FIG. 9A  illustrates shear slippage along existing weak zones like faults  96 , fractures and joints caused by perturbation of the reservoir fluids with production and injection activities. The microseismic source locations or hypocenters  98  that are detected over the production time form linear clusters  100  along fault zones forming preferential fluid flow pathways  102 , which can be mapped as shown in  FIG. 9B  by the system  10  and method of the present invention. 
       FIGS. 10A-10D  illustrate data from a microseismic experiment conducted in Saudi Arabia. Recorded traces from a surface sensor  18  and one from a shallow borehole sensor  20  are shown in  FIGS. 10A-10B , respectively, illustrating that the same microseismic event was detected in both types of sensors  18 ,  20 . A P-wave arrives first because of its faster velocity, followed by S-waves from the same microseismic event. The first arrival time difference between S-waves and P-waves provides a measure of the source distance to the respective sensor. The polarization analysis hodograms generated by the method as shown in  FIG. 10D  is a measure of azimuth and dip vectors from which the direction of the source to the sensor can be inferred using, for example, the characteristic properties of the reservoir  14 , shown in  FIG. 10C , reflecting the relation between amplitude and frequency of the emissions  55  of the microseismic events  44 , for example, as shown in  FIG. 2 . The x, y, z location for the microseismic event  44  is derived by known data processing methods, and the initiation time for the event is obtained from the GPS synchronous time using the GPS receiver and clock  72 . 
       FIG. 11  illustrates a flowchart of processing flow for microseismic data recorded on the surface  22  and in levels in a borehole  11 . The data processing procedure for each type of sensor  18 ,  20  performs a signal processing scheme followed by polarization analysis, and then computation of microseismic attributes related to the source in the reservoir  14 . For the surface sensors  18 , the data for the surface-sensor detected multi-component microseismic signal is recorded in step  104 . Data pre-processing occurs in step  106  in which the sum of such recorded microseismic data is summed over time windows, and seismic migration analysis is applied to determine the position of the microseismic events in space using an overburden layer velocity method. The grid-based volume of migrated seismograms are analyzed in step  108  for determining the origin time of the microseismic source. 
     For the borehole sensors  20 , the data for the borehole-sensor detected multi-component microseismic signal is recorded in step  110 . Data pre-processing occurs in step  112  in which P-wave and S-wave events are detected in the recorded seismograms, arrival times of microseismic events is estimated, and an auto-search is performed around the estimates for refined origin times of the microseismic events. The event parameters of the microseismic events are analyzed in step  114  for determining the source location at each origin time of the microseismic event. 
     The method then processes in step  116  the results of the analysis steps  108 ,  114 , in which source location differences is evaluated between modeled source locations with moment tensors from recorded seismograms. A best-fit solution for locations for the microseismic events is determined in step  118  with the locations being resolved in space and time (x, y, z, T O ) relative to the time of occurrence T O  of the detected microseismic events. 
     Since the sensors  18 ,  20  are recorded in time synchronously, microseismic activity related to each event is recorded by all sensors  18 ,  20  and can be identified. Such redundancy in detecting of the events improves the confidence in locating their source. The spatial distribution provides increased aperture in measurement of the microseismic events. 
     Generation of microseisms can be induced by the failure or shear-slippage by stress changes in reservoirs with perturbation caused by injection and production.  FIG. 12  is a graphic representation of the seismic data of shear slippage of reservoir rocks, due to the flow of water being injected into the reservoir rocks to produce oil. Passive microseismic events are detected by the 3-component seismic sensors  18 ,  20  planted on the surface and in the borehole, with the time-dependent behavior of such P-waves and S-waves determining the shear slippages of reservoir rocks, as shown in  FIG. 13 . The locations of hypocenters  98  of the detected microseisms are resolved mathematically for mapping by the system  10 , as shown in  FIG. 9B , and provide a distribution of a zone weakness or fluid conduit path through which the reservoir fluids advance faster than through other areas in the reservoir volume. 
     By operating a fluid injection system shown, for example, in  FIG. 2 , controlled stimulation of the reservoir  14  is performed, in which cyclical injection of fluids in predetermined start-stop cycles occurs in the injection well  26  during a calibration procedure for the plurality of seismic sensors. The detected microseismic events from such controlled injection create a plurality of vertical seismic profiles (VSP)  120 . Accordingly, predetermined locations and timing of the microseisms are processed for calibration of the sensors  18 ,  20  to orient data measurements gathered by the sensors  18 ,  20 , such as the permanent 3-component sensors, to operate in the field during the typical reservoir production life. Azimuthal VSP data at different offsets with controlled surface vibroseis sources are used to orient the x, y components in the borehole and in test sensor couplings. 
     In conventional applications, such microseisms are only detected with borehole sensors  20  in a borehole  11 . In the prior art, the restriction to only use borehole sensors  20  has limited the aperture or volumetric area that can be investigated. The present invention of the disclosed system  10  and method allows the mapping of fluid flow anisotropy over a reservoir volume, between and away from the wells. This information can also be applied to infer reservoir properties such as permeability and reservoir connectivity for numerical simulation of fluids, as shown in  FIGS. 10A-10D . The result is increased accuracy in reservoir model descriptions and improved recovery of original oil in place. 
     The system  10  and method of the present invention permits three dimensional (3D) reservoir monitoring continuously and in real-time as the fluids are produced or extracted from and injected into the reservoir  14 . The distributed network of permanent surface sensors  18  and permanent multi-level borehole sensors  20  in a single borehole  11  are used to acquire synchronized GPS time-stamped microseismic data. Universal time or GMT is obtained from at least one GPS satellite receiver  72  that is operatively connected to and/or in communication with recording device and processing systems described herein. The data from the entire network of sensors  18 ,  20  are recorded simultaneously in a central recording system. Each sensor  18 ,  20  in the network is surveyed for its (x, y, z) location, and the sensors  18 ,  20  are precisely orientated in the same configuration before cementing in place on the surface  22  or in the borehole  11 . The orientation of the borehole sensors  20  is determined after the installation is complete. This is done by generating controlled seismic sources at measured azimuthal directions around the well, as described in connection with  FIGS. 2 and 14 . The detected first arrival microseismic signals from the known seismic azimuth source at each sensor  18 ,  20  is analyzed in order to determine its orientation. 
     From the 3-component borehole sensors  20 , the microseismic data is gathered for processing by a computer  122  as shown, for example, in  FIG. 14 , which can implement the seismic server  62  in  FIG. 1 . A communication interface  124  connects to the “WIFI” communications devices  61 , and the microseismic data is acquired by a processor  126  for storage in a memory  128 , which can implement the data storage device  65 . The processor  126  and memory  128  can be implemented by any known computing system, such as a microprocessor-based server or personal computer. 
     A data analysis program  130  is provided in the memory  128  and executed by the processor  126  for performing the operations, steps, and features of the system  10  and method described herein. For example, the processor  126  can include, as hardware and/or software, tomographic analysis means  132  known in the art for generating tomograms corresponding to the acquired microseismic data. The computer  122  can include or be connected to a GPS system  134 , which can incorporate or be connected to the GPS system  72 , for managing the received microseismic data according to location and time of acquisition. 
     The computer  122  can include and/or be connected to an output device  136  which can include a display  138  and/or a printer  140  or other known output devices, such as plotters. Once the system  10  has processed the microseismic data using the data analysis program  130  and/or the tomographic analysis means  132 , with such microseismic data having been received at the processor  126  via the communications interface  124 , the processor  126  can generate and output a graphical mapping of the detected hypocenters  98  and determined flow pathways  102 , shown in  FIG. 9B . The outputted mapping shown in  FIG. 9B  can be displayed to the user on the display  138  and/or can be printed on a printer  140  or plotted using a plotting device. 
     Using the computer  122  implementing the system  10  and method of the present invention, estimates of microseismic source or hypocenter location  98 , such as shown in  FIG. 9B , are made by picking the first arrival times of P-waves and S-waves events, or first breaks, from the recorded seismograms. Hodogram analysis, such as shown in  FIG. 10D , provides the polarization direction of the P-waves and S-waves, and the velocity of the rocks obtained from other measurements in the area are used for tomographic inversion of the picked travel times to obtain the range for the source point of the microseismic event or the hypocenter  98 . 
     The hypocenters  98  from all events emanating from the reservoir  14  are mapped spatially as shown in  FIG. 9B  to form a cluster of points of all the detected microseismic events. The events, however, are too weak to be detected on individual surface sensors  18 . Records of seismic traces from a large number of surface receivers incorporating the sensors  18  are processed by stacking or adding their seismic energy over a recording time period after properly migrating or imaging the recorded amplitudes, as described in connection with step  106  in  FIG. 11 . For each microseismic event, a higher energy that is above the ambient noise floor is detected after stacking and migrating the data. 
     The hypocenter location is computed from a combination of events detected in the borehole sensors  20  and in the surface network of surface sensors  18 . The magnitude of the microseismic event determines the relative amplitude of the seismic data. The stacking or summing of the amplitude value can represent the cumulative energy from several seismic events. A 3D volume of the cumulative energy over a period of recorded time is obtained that is integrated with the distribution of hypocenter clusters obtained from the borehole sensor recording. The smaller magnitude micro-earthquakes triggered by the fluid movement are more numerous and are most important for the monitoring of reservoir changes due to injection and production activities. Events are recorded simultaneously at all sensors in the acquisition system with a source-to-receiver delay from the initiation time of each event. 
     In order to attain optimum coupling and a high signal-to-noise ratio, the surface sensors  18  are buried approximately ten feet below the earth&#39;s surface and embedded in bentonite and cement grout. The borehole sensors  20  are either cemented or clamped in place at appropriate intervals in the well  12 . Since these microseismic vibrations are extremely faint, physical coupling of the sensors  18 ,  20  to the formation and the accuracy of the geophones  28  in responding to three-component ground-particle motion are critical. 
     In the practice of the invention, a high density microseismic network is designed that uses the sensors  18 ,  20  spatially distributed on the ground surface  22  and in the borehole  11  at various levels in a monitor well  84 , which can be a dedicated well for monitoring and/or can be a production well  12 . Triaxial or 3-component geophones  28  capable of measuring artifact-free responses over a frequency range of 10 Hz to 500 Hz are employed. The sensor elements are oriented mutually orthogonally to each other. This ensures the detection of microseismic waves with particle motion in all orientations. The sensors  18 ,  20  detect microseismic source events  44  that generate microseismic emissions  55  which radiate from the rock-failure surface  16  and emanate from within the reservoir  14 . 
     Fluid movements due to production and injection operations induce microseismic events that result from elastic failure of the reservoir rock matrix. The rock failure is due to shear stress release along zones of weakness in the reservoir. Such zones of weakness are present in abundance in a heterogeneous carbonate reservoir rock matrix such as limestone and dolomite. The stress release is due to perturbation caused by reservoir fluid production and injection operations. 
     The injection operations generate an increase in reservoir pore pressure which increases the shear stress and affects the stability along the planes of weakness in reservoir rocks such as joints, bedding planes, faults and fractures. Similarly, reservoir production operation or fluid withdrawal creates a pore pressure sink which affects the stability along the zones of weakness. 
     The present invention defines a technique for the mapping of preferential fluid movement directions in the reservoir  14 . This information between the well locations cannot easily be measured in the prior art. The results of the present invention provide the orientation and distribution of preferential fluid pathways  102  such as faults shown in  FIG. 9B . Such three-dimensional fluid pathways can improve reservoir management and optimize the efficiency of fluid injection and production operations. 
     The plurality of multi-component seismic sensors  18 ,  20  is deployed in a network grid pattern and is permanently cemented just below the ground surface  22 , as shown in  FIG. 1 . Simultaneously, arrays of multi-component seismic borehole sensors  20  are placed at multiple levels in a vertical borehole  11 . The borehole sensors  20  in the borehole  11  are also cemented or clamped in place to ensure good coupling with the formation layers, as shown in  FIGS. 3 ,  3 A and  3 B. The combination of surface sensors  18  and borehole sensors  20  forms the total network for microseismic detection. The sensors  18 ,  20  continuously detect microseismic emissions  55 , generated from microseismic source events  44 , which emanate from the hydrocarbon reservoir  14  during the production life and operation of drilling to the hydrocarbon reservoir, as shown in  FIG. 5 . The sensors  18 ,  20  are connected to a plurality of remote transmission lines as the connectors  38 , and to a digitizer processor and/or an analog-to-digital converter  68 . Each sensor output is recorded on an individual channel in a multi-channel recorder, as shown in  FIGS. 6-7 . The recorded data traces are processed, as described herein. 
     Microseismic analysis techniques, which are well known in the industry, are adapted to integrate the high density measurements at the surface  22  with those made in the borehole  11  for the purpose of determining the microseismic events radiated from the source location. For each microseismic event, it is first necessary to determine the slip direction or source mechanism before analyzing for source parameters, shown in  FIGS. 10A-10D . 
     The first arrival times of the compressional or P-waves and shear or S-waves from the source, measured at the sensors  18 ,  20  and the seismic wave velocity model from source to the sensors  18 ,  20  for P-waves and S-waves, are used for resolving the source locations using a tomographic technique performed by the tomographic analysis means  132 . The difference between the arrival times of P-waves and S-waves provide the distance between the source and receiver locations. The direction of the microseismic source-to-receiver is inferred from the P-wave particle motion hodograms. The frequency spectrum of the recorded microseismic signals provides a measure of magnitude of the zone of shear slippage in the reservoir  14 , as shown in  FIGS. 10A-10D . 
     A field experiment was conducted over a producing oil field in Saudi Arabia to assess the feasibility of monitoring microseismic activity related to the subsurface reservoir at depth. Two shallow wells were drilled for the purpose and were instrumented with 3-component borehole sensors  20 . Similar sensors  18  were also deployed in a spatial pattern on the ground surface  22 . Simultaneous observations of the ambient microseismicity on the ground surface  22  and at various levels in the two boreholes  11  were made at the test site over several days. Using a velocity model developed from measurements at various wells drilled previously in the location and the laboratory analysis of the geomechanical properties of rock core samples, the microseismic emissions  55  emanating from the reservoir  14  were estimated. This data was compared with observed microseismicity at the network of sensors  18 ,  20 . 
     Analysis of the results from the experiment indicates that the observed ambient noise levels in the pilot test area in Saudi Arabia are sufficiently low. This result also indicates that a microseismic network consisting of surface sensors  18  and borehole sensors  20  is able to detect extremely low intensity microseismic events with local magnitude M L &lt;−2 from the reservoir levels. The results also indicate that attenuation of recorded microseismic activities is very low, indicating a high Q factor. The low attenuation improves the prospect of detecting minute microseismic events  44  over long source-to-receiver travel paths. This makes the study area in Saudi Arabia an ideal location for the microseismic experiment. 
     In order to obtain the advantages of features in the present invention, a total network of a large number of surface 3-component sensors  18  in a spatial array, such as shown in  FIG. 4 , and borehole sensors  20  in a vertical array are installed, as shown in  FIG. 1 . These are permanently cemented in place for maximum coupling with the earth formations. The location of each sensor  18 ,  20  in 3D space is surveyed and the sensors  18 ,  20  are precisely oriented. All horizontal sensors are oriented in a common direction. All the sensors  18 ,  20  are connected to an electronic amplifier  66  and an analog-to-digital converter  68  or to a digitizer. This converts the detected analog vibrations or seismic emissions  55  to digital values that are recorded by a multi-channel data acquisition unit  70  or by the recording system. Each sensor  18 ,  20  is recorded in a specific channel of the multi-channel data acquisition unit  70  shown in  FIG. 5 . 
     The recorded data are sent in real-time via a dedicated “WIFI” wireless communication device  61 . The continuous data acquisition unit is connected to a GPS receiver and clock  72  that time-stamps microseismic events  44  detected by each sensor  18 ,  20  shown in  FIG. 5  with a standard time such as the Greenwich Mean Time (GMT) obtained from GPS satellites. The first arrival times of the P-wave and the S-wave are determined from the data records during data processing. 
     The recorded data are analyzed for the hodograms to compute the azimuth and dip for the seismic waves arriving at the sensors  18 ,  20 . The hodograms are used to calculate the microseismic event source point or location of the hypocenter  98  by converting the time to depth using a velocity model for the area that is deduced from well measurements in the vicinity. The spectral frequency of the signal is used for estimation of the radius of rock failure and the polarity hodogram and relative amplitudes of the seismic signal components that indicates the orientation of the elastic deformation surface, shown in  FIGS. 10A-10D . 
     The computation of location of microseismic sources is performed by techniques known in the art, such as known and commercially available computer software for such analysis. The location in (x, y, z) coordinates for each microseismic event  44  that is detected by the surface sensors  18  and the borehole sensors  20  is derived, and its time of occurrence T O  is obtained from the GPS time stamp from the recording system. The plurality of sensors  18 ,  20  in a high density network provides the redundancy in the recorded data and improves the accuracy in the source location of the detected events. 
     The system  10  and method of the present invention include a network of a large number of high density microseismic sensors  18 ,  20  installed on the surface  22  and at various levels in the borehole  11 . The network of sensors  18 ,  20  is calibrated by stimulating the reservoir thus inducing microseismic events as shown in  FIG. 2 . This is done by performing injector pulse tests which constitutes starting and stopping water injection in nearby injection wells  26 , at predefined intervals, shown in  FIG. 8 . Explosive charges could also be detonated in a nearby well at predefined depth levels in the reservoir  14 . The resulting shock waves are detected at the surface sensors  18  and borehole sensors  20  as seismic events with a delay time corresponding to the distance of each respective sensor  18 ,  20  from the source location. 
     As injected water displaces the oil that is extracted, the zones of weakness in the reservoir rocks such as joints and faults are perturbed, and a local microseismic event  44  is generated in the reservoir volume, as shown in  FIG. 2 . The reservoir volume is idealized to be composed of a large number of small equal-size cubes where the cubes represent the reservoir matrix. These cubes or grid blocks in this cellular model either contain a shear slippage with resulting microseismic activity or has no activity. When contiguous grid blocks contain microseismic events  44  generating microseismic emissions  55  emanating from within, such microseismic events are likely to be due to a system of fractures that have been temporarily or permanently displaced by the fluid flow from water injection or oil production. These cells with microseismic activities would therefore be interconnected to hydraulic flow and would constitute fluid flow pathways  102  along these preferential directions, such as faults, shown in  FIG. 9B . Grid blocks having no microseismic activity are the reservoir zones with no preferential fluid flow directions or isotropic flow shown in  FIG. 1 . 
     By continuously interrogating all the cells in the reservoir volume for recorded microseismic activities in the sensors  18 ,  20  deployed in the borehole  11  and those spatially deployed on the ground surface  22 , an estimate of the flow anisotropy and permeability can be made empirically. The network of microseismic events forms a conductivity network that could serve as input for reservoir simulation in order to compute fluid flow through such network. 
     The microseismic emissions from the reservoir  14  are calibrated by correlating with induced activity in the reservoir  14 . The rates of fluid injection and production in the reservoir  14  are varied or “pulsed” at the well locations and their effects on detection and recording of microseismicity in the monitor well  84 , and the surface sensors  18  are monitored as shown in  FIG. 2 . The microseismicity detected above the ambient noise threshold due to such controlled pulsing of reservoir provides a correlation with the reservoir pressure and flow rate. The processed microseismic attributes also need to be correlated with the spatial distribution of surface sensors  18  and the vertically oriented borehole sensors  20  in the monitor well  84 . 
     The processing of the microseismic system  10  consists of the signal processing of recorded seismograms collected from the surface  22  and the borehole sensors  20 , and integrating the results of the total system. The surface data is summed over time windows, the recorded seismic energy in the data is migrated using a velocity model in the area of study and epicenters locations for the microseismic events and their recorded time of occurrence is corrected. These epicenters of microseismic events are related to the hypocenters  98  of events derived from processing of the microseismic recording in the borehole sensors  20 . The time synchronous events for the hypocenters  98  located in the reservoir depths for the two sensor systems of the surface sensors  18  and borehole sensors  20  are matched for interpretation of shear slippage in the zones of weakness in reservoir rocks. This shear slippage is due to perturbation of the reservoir fluids by injection and production operations. Thus, a mapping of such shear slippage and faults which serve as fluid pathways  102 , such as shown in  FIG. 9B , is generated and output to the user by the discloses system  10  and method. 
     While the preferred embodiments of the present invention have been shown and described herein, it will be obvious that each such embodiment is provided by way of example only. Numerous variations, changes and substitutions will occur to those skilled in the art without departing from the invention disclosed. Accordingly, it is intended that the invention be limited only by the spirit and scope of the appended claims.