Patent Application
20140019057
Various embodiments described herein relate to the field of seismic data acquisition and processing, and devices, systems and methods associated therewith.
Microseismic monitoring of hydraulic fractures is the study of very small seismic events, typically less than Richter magnitude 0, that are induced during hydraulic fracturing. Hydraulic fracturing is the process of creating or enhancing fractures in rock formations by pumping high pressure fluid and proppant into the rocks, thereby increasing the ability to produce hydrocarbons from the rock formation. The purpose of microseismic monitoring is to determine if the hydraulic fracturing has unintended effects such as opening fractures into shallow layers and freshwater aquifers, and to determine if the hydraulic fracturing has the intended effects within the hydrocarbon-bearing rock formation. Microseismic monitoring may be performed in real time during the hydraulic fracturing operation, in which case the fracturing operation can be modified or stopped if unintended fracturing effects are evident.
Microseismic monitoring is typically performed by placing arrays of geophones in adjacent wells, or at or near the earth's surface. These instruments sense the ground motion caused by the microseismic events, which is then used to determine the event location. Microseismic events produce very small ground motions, and surface or near-surface microseismic monitoring is limited by noise contamination. Noise contamination includes surface waves, refracted waves, and reflected waves from surface noise sources. Noise contamination masks microseismic signals, and noise contamination can lead to the false identification of microseismic events.
What is desired are improved techniques wherein microseismic data are acquired and processed in such a manner that real microseismic events can be distinguished from noise and false microseismic events, thereby allowing detection and location of more and smaller microseismic events. The resulting improvement in the confidence level associated with the microseismic events enables better determination of event locations that in turn may more accurately represent the effects of hydraulic fracturing, while avoiding false events that may misrepresent the effects of hydraulic fracturing.
In one embodiment, there is provided a method for discriminating between small microseismic events and false events comprising: obtaining a set of microseismic data traces recorded at a plurality of receivers; identifying at least one candidate event by applying a source scanning algorithm; for each candidate event; identifying an apparent location of the candidate event; correcting the microseismic data traces for the travel times from the apparent location of the candidate event to each corresponding receiver; organizing the time-corrected traces into a plurality of groups of traces; creating a plurality of sub-stack traces from the traces within each group and analyzing the sub-stacks to classify the candidate event as a microseismic event or a false event.
In another embodiment, there is provided a method for discriminating between small microseismic events and false events comprising: obtaining a set of microseismic data traces recorded at a plurality of receivers; identifying at least one candidate event by applying a source scanning algorithm; for each candidate event; identifying an apparent location of the candidate event; correcting the microseismic data traces for the travel times from the apparent location of the candidate event to each corresponding receiver; organizing the time-corrected traces into a plurality of groups of traces; creating a plurality of sub-stack traces from the traces within each group and analyzing the reverberations in the sub-stacks to classify the candidate event as a microseismic event or a false event.
In a further embodiment, there is provided a method for discriminating between small microseismic events and false events comprising: obtaining a set of microseismic data traces recorded at a plurality of receivers; identifying at least one candidate event by applying a source scanning algorithm; for each candidate event; identifying an apparent location of the candidate event; correcting the microseismic data traces for the travel times from the apparent location of the candidate event to each corresponding receiver; organizing the time-corrected traces into a plurality of groups of traces; creating a plurality of sub-stack traces from the traces within each group and analyzing polarity reversals in the sub-stacks to classify the candidate event as a microseismic event or a false event.
Further embodiments are disclosed herein or will become apparent to those skilled in the art after having read and understood the specification and drawings hereof.
Different aspects of the various embodiments of the invention will become apparent from the following specification, drawings and claims in which:
The drawings are not necessarily to scale. Like numbers refer to like parts or steps throughout the drawings.
In the following description, specific details are provided to impart a thorough understanding of the various embodiments of the invention. Upon having read and understood the specification, claims and drawings hereof, however, those skilled in the art will understand that some embodiments of the invention may be practiced without hewing to some of the specific details set forth herein. Moreover, to avoid obscuring the invention, some well-known methods, processes and devices and systems finding application in the various embodiments described herein are not disclosed in detail.
Referring now to the drawings, embodiments of the present invention will be described. The invention can be implemented in numerous ways, including for example as a system (including a computer processing system), a method (including a computer implemented method), an apparatus, a computer readable medium, a computer program product, a graphical user interface, a web portal, or a data structure tangibly fixed in a computer readable memory. Several embodiments of the present invention are discussed below. The appended drawings illustrate only typical embodiments of the present invention and therefore are not to be considered limiting of its scope and breadth. In the drawings, some, but not all, possible embodiments are illustrated, and further may not be shown to scale.
For the first 100 years and more of oil exploration and production, wells were drilled almost exclusively in geologic formations that permitted production of oil and gas flowing under the natural pressures associated with the formations. Such production required that two physical properties of the geologic formation fall within certain boundaries. The porosity of the formation had to be sufficient to allow a substantial reserve of hydrocarbons to occupy the interstices of the formation, and the permeability of the formation had to be sufficiently high that the hydrocarbons could move from a region of high pressure to a region of lower pressure, such as when hydrocarbons are extracted from a formation. Typical geologic formations having such properties include sandstones.
In recent years, it has become apparent that large reserves of hydrocarbons are to be found in shale formations. Shale formations are typically not highly permeable, and therefore present formidable obstacles to production. The most common technique in use today that permits commercial production of hydrocarbons, and especially natural gas, from shale formations, is hydraulic fracturing. This technique can be also be applied to older wells drilled through non-shale formations to increase the proportion of hydrocarbons that can be extracted from them, thus prolonging the productive life of the well. Hydraulic fracturing was developed in the late 1940s, and has recently become much more widely used in the development of shale gas and oil.
Hydraulic fracturing involves pumping fluid under very high pressure into hydrocarbon-bearing rock formations to force open cracks and fissures and allow the hydrocarbons residing therein to flow more freely. The fluid is primarily water, and may contain chemicals to improve flow, and also “proppants” (an industry term for substances such as sand). When the fracturing fluid is removed, and the hydrocarbons are allowed to flow, the sand grains prop open the fractures and prevent their collapse, which might otherwise quickly stop or reduce the flow of hydrocarbons.
The progress of a fracturing operation must be monitored carefully. Well fracturing is expensive, and the fracturing process is frequently halted once its benefits become marginal. The high pressures associated with fracturing result in fractures that tend to follow existing faults and fractures, and can result in an uneven or unpredictable fracture zone. Fracturing fluid may also begin following an existing fault or fracture zone and then propagate beyond the intended fracture zone. Care must be taken not to interfere with existing production wells in the area. For these and other reasons, it is important that the fracturing operator be able to follow accurately the progress of the fluid front in the subsurface while the fluid is being injected into the well. Monitoring the fracturing process allows the operator to optimize the process and potentially to recover more gas or oil from the formation than would otherwise be possible. Techniques to monitor the hydraulic fracturing were introduced in the 1970s. See U.S. Pat. No. 3,739,871 to Bailey entitled “Mapping of Earth Fractures Induced by Hydrafracturing”, the disclosure of which is incorporated herein in its entirety.
Conventional surface seismic reflection surveys generally do not work well for monitoring the movement or positions of fluid fronts in the subsurface. The physical dimensions of fractures are often shorter than can be detected using conventional surface seismic reflection techniques. In addition, within a given geologic formation there may be no or low contrasts in seismic velocity, and as a result surface seismic reflection techniques cannot be used effectively to image fractures within the formation. Fractures also tend to scatter seismic energy, further reducing their detectability by conventional surface seismic reflection means.
An alternative approach to the problem of imaging fractures or fluid fronts within formations is known as “microseismicity”. Instead of using “active” surface seismic energy sources, “passive seismic” techniques are used to detect the times and locations of the origins of seismic energy generated in the subsurface of the earth by hydraulic fracturing. Seismic energy emitted by fracturing of a geologic formation, caused by the injection of high pressure fracturing fluid into the formation, is sensed and recorded. The objective then becomes determining the point of origin of the emitted seismic energy, which defines the location of the fracture. One method of locating fractures and faults in geologic formations is known as Seismic Emission Tomography (SET). Examples of SET techniques and processes are described in U.S. Pat. No. 6,389,361 to Geiser entitled “Method for 4D permeability analysis of geologic fluid reservoirs” (hereafter “the '361 patent”) and in U.S. Pat. No. 7,127,353 to Geiser entitled “Method and apparatus for imaging permeability pathways of geologic fluid reservoirs using seismic emission tomography” (hereafter “the '353 patent”), the disclosures of which are hereby incorporated by reference herein in their respective entireties.
Neither the time nor the exact location of the microseismic events are known in advance, and therefore monitoring must be continuous and must be performed over a wide area. Methods have evolved that require listening for extended periods of time, that is, hours, days or weeks, and using various algorithms to extract the very low level signals from the background noise. Data are recorded over an extended time period, with the duration of recording and the sampling interval being controlled by the objectives of the seismic data acquisition process, the characteristics of the events that generate the detected or sensed seismic energy, the distances involved, the characteristics of the subsurface, and other factors.
The data at each sensor are recorded as a time series of amplitude values corresponding to the seismic energy detected at the sensor. Such time series are referred to as “traces”. The data recorded at each sensor location are then filtered and processed using various processing techniques and software, which convert the data into a series of values within gridded subsurface volumes corresponding to multiple time samples. The values of the points in the grid represent attributes of the data, which values vary over time corresponding to variation in the energy emitted at each point in the subsurface.
A hydraulic fracturing operation is shown in progress in horizontal wellbore 60. Under the control and direction of well operation control center 32, hydraulic fracturing fluid is pumped at high pressure through pipe 34 into vertical wellbore 30 and hence into horizontal wellbore 60. The high pressure forces fracturing fluid out through perforations in wellbore 60 into zones 62 in hydrocarbon producing geologic formation 5 around wellbore 60. The high pressure of the fluid creates fractures or enhances existing fractures in surrounding subsurface volume 40 within formation 5, causing one or more releases of seismic energy at point of fracture 42. The fracturing process can be repeated multiple times at different locations within wellbore 60 to fracture additional zones 64.
This seismic energy propagates from point of fracture 42 through subsurface 15 of the earth as a series of acoustic wavefronts or seismic waves 44, which are then sensed by surface sensors 12 disposed along surface 8 and/or downhole sensors 22 disposed in borehole 20, converted into electrical, optical and/or magnetic analog or digital signals, and recorded by data acquisition and recording system 10 using techniques and equipment well known in the art. The electrical, magnetic, or optical analog or digital signals generated by sensors 12 and 22 are proportional to the displacement, velocity or acceleration of the earth at locations corresponding to sensors 12 and 22, where such displacement, velocity or acceleration is caused by seismic wavefront 44 arriving at the locations of sensors 12 and/or 22, and are recorded as data by recording system 10. As further shown in
According to one embodiment, data may be recorded, processed and analyzed or interpreted while fracturing is occurring, thereby enabling near-real-time monitoring of the fracturing process.
Note that
In other embodiments, signals generated by sensors 12 and/or 22 are transmitted by wireless transmitters to a receiver operably connected to data acquisition and recording system 10. In still other embodiments, the electrical, magnetic and/or optical signals generated by sensors 12 and/or 22 are stored as data in solid state or other memory or recording devices associated with one or more sensors 12 and/or 22. The memories or recording media associated with the recording devices may be periodically collected or polled, and the data stored therein uploaded to data acquisition and recording system 10.
Other embodiments include, but are not limited to, the recording of the seismic waves created by the energy released by explosive charges during the perforation of vertical wellbore 30 or horizontal wellbore 60. When vertical wellbore 30 and horizontal wellbore 60 are cased with a metal pipe or casing, the casing must be perforated so that oil or gas may flow into pipe 34 and thence to surface of the earth 8 at wellhead 38. Small explosive charges are used to perforate the casing and create perforations through which oil or gas may then flow. Perforation is also required before a hydraulic fracturing operation can take place, to allow the hydraulic fracturing fluids to flow into the surrounding formations.
Still other configurations and embodiments may be employed to locate, measure and analyze faults in the subsurface of the earth by microseismic detection and processing means, such as, for example, sensing, recording and analyzing seismic energy originating from naturally occurring events, such as slippage along faults, settling or tilting of the subsurface, earthquakes, and other naturally-occurring events.
Data recorded by data acquisition and recording system 10 are typically, although not necessarily, in the form of digitally sampled time series commonly referred to as seismic traces, with one time series or seismic trace corresponding to each sensor 12 or 22. Each value in the time series is recorded at a known time and represents the value of the seismic energy sensed by sensors 12 and 22 at that time. The data are recorded over a period of time referred to as the data acquisition time period. The data acquisition time period varies depending on the objective of the seismic survey. When the objective of the survey is to monitor a fracturing operation, for example, the data acquisition time period may be in hours or even days. When the objective of the survey is to acquire data associated with perforating a well, the data acquisition time period is much shorter and may be measured, by way of example, in seconds or minutes.
It is usual to record more data than is required for a given survey objective. For example, when monitoring a fracturing operation, recording may begin several minutes before the fracturing operation is scheduled and continue until a time beyond which it is unlikely that any further energy will be released as a result of the fracturing process. Such a process may be used to record the ambient seismic field before and/or after fracturing, production, halt of production, or perforation operations.
Once the seismic data have been recorded, they must be processed and converted to produce a useful display of information. In at least some microseismic data processing techniques, the Source Scanning Algorithm or some variation of the algorithm is used to determine the point at which the microseismic energy originated.
In
If, however, the same process is applied at subsurface location η′, at time τ, the result is different. If microseismic event 212 had occurred at (η′,τ) in the subsurface at point η′ and time τ, then the travel time for the seismic energy 220 to reach station A 204 would be taη′. Similarly, the travel times to station B 206 and station C 208 would be tbη′ and tcη′ respectively. Energy 220 from the microseismic event would be expected to arrive at the surface sensors at times (τ+taη′), (τ+tbη′) and (τ+tcη′). As shown in
Semblance is a measure of the similarity of seismic traces, and is defined as the energy of the stacked trace divided by the mean energy of all traces that contribute to the stack. See “Semblance and Other Similarity Measurements”, M. T. Taner, Rock Solid Images, November 1996, the disclosure of which is incorporated herein in its entirety. If fi j is the j th sample of the i th trace, then the semblance coefficient Sc is
where M traces are summed; and the coefficient is evaluated for a window of width N samples centered at time sample k.
As shown in
Data are recorded at N sensors 310 on surface 312 as a series of times and amplitudes, the time series for each sensor being referred to as a “trace”. The time values correspond to the time at which the seismic energy arrived at the sensor, which must be later in time than when the seismic energy was emitted from the source in the subsurface. Using a known or estimated velocity model, the travel time and travel path from the voxel to each sensor is computed for each voxel 302 in subsurface grid 300. A set of data is selected, corresponding to a chosen time interval. For each voxel 302 in subsurface grid 300, the trace recorded at each of the N sensors 310 has the appropriate computed travel time shift applied to it. Thus the seismic energy for each trace is corrected in time to the time when it was emitted. The result is a set of N traces which may be considered to have originated at this voxel 302. These traces are then summed or “stacked” together.
Where the voxels coincide with the location of actual microseismic events the microseismic event energy is “flattened”, or aligned in time, by the subtraction of the travel times, and the energy from each trace will add when the traces are stacked, thereby representing an event location. If no microseismic event occurred at this voxel, then the resulting stacked trace will show the random background noise. This process is repeated for each voxel in the subsurface volume of interest.
In other implementations of the source scanning method, the semblance of the N time-shifted traces is computed. The semblance function shows the similarities between traces, and has a high value if a seismic event originated at the voxel, and a low value if there is nothing more than random background noise at this voxel. The result is a representation of the subsurface for the selected time interval showing where microseismic events may have occurred. Yet other implementations use different attributes of the data.
While various algorithms may be used to transform the acquired data, the end result is typically the same: a series of spatial volumes are produced, where each spatial volume is associated with a given data subset, and each data subset corresponds to a given time window. The values corresponding to the voxels within the spatial volume represent the amount of energy emitted from each voxel during a given time window. The energy emitted from each voxel during a given time window may be represented by different attributes of the data, including, but not limited to, semblance, amplitude, absolute amplitude, reflection strength (the amplitude of the envelope of the seismic wave), polarity or apparent polarity, phase, frequency, and other attributes of seismic data which will be apparent to those skilled in the art. See “Complex seismic trace analysis”, M. T. Taner, F. Koehler, and R. E. Sheriff, Geophysics, Vol. 44, No. 6 (June 1979), pp 1041-1063, hereinafter “Complex seismic trace analysis”, the disclosure of which is incorporated herein in its entirety.
Typically the energy released during hydraulic fracturing is of a very low level, usually below zero on the Richter scale, hence the amount of energy that reaches the surface and is detected by the surface sensors is extremely small. Surface or near-surface microseismic monitoring is limited by noise contamination, as shown by many authors. See “Comparison of surface and borehole locations of induced seismicity”, Eisner et al., Geophysical Prospecting, Vol. 58, Issue 5, pp 809-820, September 2010, the disclosure of which is incorporated herein in its entirety. See also “Comparison of simultaneous downhole and surface microseismic monitoring in the Williston Basin”, Diller and Gardner, 2011 Annual International Meeting, SEG, Expanded Abstracts, the disclosure of which is incorporated herein in its entirety. The presence of a noise burst or spike on one trace can create a high value in the stacked data which may be falsely interpreted as a microseismic event. Hence the results of conventional microseismic processing contain many false events, reducing the level of confidence that may be placed in the results. The method described herein avoids these problems by creating and analyzing sub-stacks.
Although the embodiment described above describes “stacking” as the process of summing the traces, it will be understood by those of skill in the art that the term “stacking” can also refer to other methods of combining data from multiple seismic traces in such a way as to enhance the desired signal while reducing the effects of noise. The term “stacking” in this disclosure should be understood to include all methods commonly accepted within the industry of combining multiple seismic traces to produce a single trace for analysis. These methods include, but are not restricted to, summing of the trace amplitudes, computing the median, computing the trimmed mean sum, diversity stacking and various weighted stacking methods. In diversity stacking, amplitude values exceeding some predetermined threshold are excluded and amplitude values below this threshold are summed. These methods are listed as examples only and are not to be read as limitations. Other methods will be known to those of skill in the art and may be used interchangeably with the examples listed in this description.
In some embodiments of the present method, a variation of the source scanning algorithm is employed. Rather than summing or stacking the groups of traces to create sub-stacks, the semblance of groups of the time-shifted traces is computed. The semblance has a high value if a seismic event originated at the voxel, and a low value if there is nothing more than random background noise at this voxel. The result is a representation of the subsurface for the selected time interval showing where microseismic events may have occurred. Yet other implementations use different attributes of the data.
It should be noted that
Referring now to
Comparing
The reverberations for small microseismic events are harder to detect and use as criteria for distinguishing between real events and false events caused by noise bursts. In some embodiments of the present method, sub-stacks of the data traces are created as described above, and examined for reverberations. In the sub-stack data, both the microseismic event and the reverberations are more visible, enabling visual determination of whether the reverberations are present and allowing the trained observer to distinguish between real and false events.
In other embodiments, automated methods are used to discriminate between real and false microseismic events by evaluating the presence or absence of reverberations. One such embodiment uses the average of the semblance over a sliding window in time to aid in the recognition of reverberations. Other embodiments use a subset of the highest semblance values over a sliding window to aid in the recognition of reverberations.
Using sub-stacks, this same polarity effect can be seen even in small microseismic events. Each sub-stack contains traces that are close to each other, and hence will record data with similar polarity. However, the different sub-stacks may show differing polarities. It is therefore possible for a trained observer to visually identify on the sub-stacks small events that might produce very low values when all the traces were stacked, and might thus be overlooked. Further, the variation in polarity may provide information about the direction of first motion of the microseismic event, and hence information about the direction of stress in the subsurface.
Some embodiments of the present method enable recognition of polarity reversals in sub-stacks by automated methods that discriminate between small microseismic events and false events, using semblance that is computed over spatially adjacent groups of sub-stacks instead of all sub-stacks.
In other embodiments, the sub-stack traces are formed as the semblance of the traces in each group, or in yet other embodiments, from a semblance-weighted stack of the traces in each group.
The method and embodiments described above refer to surface sensors, but the method is applicable to other embodiments such as analyzing microseismic data recorded using sensors placed in a borehole. Other embodiments include applying the methods described herein to data acquired using buried arrays, wherein the data are acquired using sensors buried in shallow boreholes drilled for the purpose.
The method and embodiments described herein provide a robust method of discriminating small microseismic events from false events, where other methods have failed.
It is noted that many of the structures, materials, and acts recited herein can be recited as means for performing a function or step for performing a function. Therefore, it should be understood that such language is entitled to cover all such structures, materials, or acts disclosed within this specification and their equivalents, including any matter incorporated by reference.
It is thought that the apparatuses and methods of embodiments described herein will be understood from this specification. While the above description is a complete description of specific embodiments, the above description should not be taken as limiting the scope of the patent as defined by the claims.
Other aspects, advantages, and modifications will be apparent to those of ordinary skill in the art to which the claims pertain. The elements and use of the above-described embodiments can be rearranged and combined in manners other than specifically described above, with any and all permutations within the scope of the disclosure.
Although the above description includes many specific examples, they should not be construed as limiting the scope of the method, but rather as merely providing illustrations of some of the many possible embodiments of this method. The scope of the method should be determined by the appended claims and their legal equivalents, and not by the examples given.
| Number | Date | Country | |
|---|---|---|---|
| 61672043 | Jul 2012 | US |
