Integrated Seismic-to-Simulation Workflow Identifies Highest-Productivity Sweet Spots in Major Shale Gas Play
Summary
The Integrated Seismic-to-Simulation Workflow represents a cutting-edge approach to the identification of high-productivity sweet spots within major shale gas plays. This methodology combines advanced seismic data processing and simulation techniques to optimize hydrocarbon extraction, particularly in mature fields where infill drilling strategies can be employed to exploit bypassed pay zones.
Seismic surveys, including 2D, 3D, and 4D formats, are fundamental in mapping subsurface geological structures, offering geologists and engineers critical insights into potential hydrocarbon reservoirs. The integration of geological, petrophysical, geomechanically, and geophysical data within this workflow ensures a comprehensive characterization of shale gas plays, significantly reducing risks and uncertainties associated with exploration and production.
Technological advancements have enhanced the accuracy and efficiency of shale gas exploration. Innovations in seismic processing techniques, remote sensing, and advanced modeling software allow for more precise assessments of potential drilling sites.
These advancements are exemplified by a case study from the Montney Formation in Western Canada, where an integrated approach combining surface seismic data, elastic property volumes, petrophysical data, and micro-seismic monitoring results provided a thorough evaluation of the reservoir.
This integrated seismic-to-simulation workflow is crucial in identifying the highest-productivity sweet spots, ensuring responsible and effective resource extraction. Despite its numerous advantages, the implementation of this workflow presents challenges, such as the persistent use of outdated cable-based systems over newer nodal technologies and the complexity of terrain in seismic survey areas.
The integration of seismic data with reservoir simulation results also requires advanced data visualization and analytics software to effectively merge different datasets, highlighting the need for both advanced software and skilled personnel.
Furthermore, while 3D seismic methods offer improved image quality and greater data diversity, they are more elaborate and costly compared to 2D methods, necessitating a careful balance between cost and data quality. Looking ahead, future trends in shale gas exploration will likely leverage advanced technologies and innovative methodologies to improve efficiency and accuracy.
The continued development and application of seismic technologies, remote sensing techniques, and environmentally sustainable practices are expected to play significant roles. The industry is also witnessing a shift towards denser seismic surveys that are both cost-effective and environmentally friendly, utilizing small, light autonomous nodes for seismic data acquisition. These trends point to a future where integrated seismic-to-simulation workflows will be even more pivotal in optimizing shale gas exploration and production.
Background
Seismic surveys are a fundamental tool in oil and gas exploration, providing critical data that enables geologists and engineers to map subsurface geological structures and identify potential hydrocarbon deposits. These surveys can be conducted in 2D, 3D, and 4D formats, each offering different advantages in terms of resolution and data quality[1].
The application of 3D seismic technology has revolutionized the field by offering detailed images of the subsurface. For instance, a 3D seismic dataset from offshore Australia reveals a complex system of marine channels and related sedimentary deposits, which are critical for understanding the geology and potential hydrocarbon reservoirs of the area[2]. The inline and crossline sections in these datasets provide perpendicular views of the geological features, offering a comprehensive understanding of the subsurface structures[2].
One of the advanced processing techniques used in seismic surveys is migration, which corrects the apparent positions of subsurface features by accounting for the bending, scattering, and directional changes of seismic energy[2].
This results in sharper images that more accurately reveal the underlying geology, essential for precise evaluations of potential drilling sites. In recent years, the integration of geological, petrophysical, geomechanical, and geophysical data has become increasingly important in characterizing shale gas plays[3].
A case study from the Montney Formation in Western Canada exemplifies this integrated approach, combining surface seismic data, elastic property volumes, petrophysical data, and micro-seismic monitoring results to provide a comprehensive evaluation of the reservoir[3].
Technological advancements have also enhanced the accuracy and efficiency of shale gas exploration. Innovations such as remote sensing, advanced modeling software, and improved seismic processing techniques allow for more precise assessments of potential sites, thereby reducing risks and maximizing resource recovery[4].
This integrated seismic-to-simulation workflow is critical in identifying the highest-productivity “sweet spots” within shale gas plays, ensuring that resources can be accessed responsibly and effectively.
Integrated Seismic-to-Simulation Workflow The Integrated Seismic-to-Simulation Workflow is a sophisticated approach that integrates seismic data processing and simulation techniques to identify the highest-productivity sweet spots in shale gas plays. This workflow is particularly beneficial in mature field case studies, where bypassed pay zones can be exploited through infill drilling strategies.
Workflow Execution
The high-fidelity seismic-to-simulation workflow begins with seismic cross-equalization and extends through well planning. This method ensures consistency between the subsurface model and historical production data, reducing risks and uncertainties associated with seismic interpretations and simulation results[5].
The workflow employs depth and time-driven 4D processes to reconcile seismic and simulation data, thereby minimizing upscaling ambiguities and resampling artifacts. Techniques such as accurate velocity modeling and a priori planning of reservoir and simulation spatial grid scales are used to enhance the precision of the analysis[5].
Processing and Techniques
The processing of seismic data involves various techniques to attenuate random noise, coherent noise, and multiple reflections. Methods to mitigate these interferences include exploiting the signal uncorrelated from trace to trace, and leveraging the linearity in the frequency-wavenumber and slant-stack domains[6].
Multiples can be attenuated by using velocity discrimination techniques in the common-midpoint, slant-stack, and velocity-stack domains[6]. The Fourier transform underpins much of the digital signal processing applied to seismic data.
Processing algorithms are designed for either single-channel or multichannel time series and fundamentals of signal processing also encompass examining characteristics of seismic signals, such as primary reflections from layer boundaries and various types of noise[6].
Seismic Survey Design
Seismic survey design is influenced by factors such as the intended use of the data, desired resolution, target depth, and data quality. The selection of seismic sources and receivers, such as geophones or wireless seismic nodes, depends on the geological environment and project objectives. For instance, explosive sources are better for deep target depths, while seismic vibrators are suitable for shallow depths[7].
A 4D seismic survey utilizes 3D seismic data acquired at different time intervals to assess changes in a producing hydrocarbon reservoir, such as fluid movement, saturation, and reservoir pressure and temperature. This is especially useful for monitoring the dynamic aspects of a reservoir over time[7].
Data Acquisition and Integration
Seismic data can be acquired on land or at sea, using grids of receivers and strategically positioned sources. On land, the sources and receivers are deployed in a grid pattern, while in marine environments, sources and streamers are deployed off the back of a moving ship[2].
The collected seismic data is then analyzed to define the necessary resolution, noise levels, and geometry for the layout of the source and receiver lines. This comprehensive analysis helps in achieving good data quality and efficient survey execution[7].
Implementation in Shale Gas Play
The implementation of integrated seismic-to-simulation workflows in shale gas plays has proven critical in optimizing production and reducing risks associated with unconventional hydrocarbon extraction. Over the last two decades, hydrocarbon production from tight and unconventional plays has substantially increased, particularly in North America, where the successful extraction of shale gas and oil has significantly reduced dependence on imports [8].
This success has spurred similar activities in other regions, including the Middle East, China, and Argentina. However, the North American approach of numerous operators drilling, completing, and producing wells is not easily replicable elsewhere, necessitating a comprehensive understanding of the subsurface to de-risk these plays and improve economic outcomes [8].
Advancements in technology and operational efficiency, particularly in completion and stimulation engineering, have been pivotal in this context. In North America, major leaseholders exploring the Horn River Basin and Montney Formation in Western Canada have leveraged pre-stack amplitude variation with offset (AVO) inversion data to aid well placement and field development planning [3].
The integration of geological, petrophysical, geomechanical, and geophysical workflows has become increasingly sophisticated, enabling better shale gas characterization and more informed decision-making in field development [3].
A case study from the Triassic age Montney Formation in Western Canada highlights the benefits of such integrated workflows. This study combined surface seismic amplitude and elastic property volumes with petrophysical data and micro-seismic monitoring results, bringing more geophysical rigor to a traditionally engineering-dominated play type [3].
The hybrid model employed integrates the advantages of continuum and discrete fracture models, though challenges remain regarding complex modeling, computational efficiency, and applicability to faults and complex boundaries [9].
For instance, an operator in a major unconventional shale gas play sought to understand the factors controlling reservoir quality and production. The facies within the play varied significantly in terms of matrix quality, presence, orientation, and status of natural fractures, as well as net gas porosity along the length of laterals extending up to 5,000 feet.
Production rates varied by a factor of three or more between wells. A comprehensive, calibrated workflow was necessary to rank potential drill locations, predict production performance, plan drilling, and design completions [10].
Furthermore, the location of shale gas deposits is intricately linked to geological formations and structures. Shale gas is typically found within specific sedimentary rock formations formed under unique geological conditions over millions of years.
Understanding these formations, including their composition, age, thickness, and extent, is essential for determining the presence of shale gas [4].
Seismic data plays a crucial role in identifying these formations and hypothesizing sweet spot locations, though confirmation via pilot wells is necessary. Structural variations are easier to identify using seismic data, with seismic attributes highlighting frequency variations being particularly useful for predicting microfractures within a shale play [11].
Role of Reflection Seismology
Reflection seismology is a crucial technique for imaging strata within the subsurface, providing detailed insights into geological structures and stratification[2]. This geophysical method involves generating seismic waves at or near the Earth’s surface using various seismic sources such as dynamite, hammers, vibrators, air guns, and water guns[2].
These waves propagate through geologic layers, and at interfaces between different rock types, they undergo changes in physical properties like density and seismic velocity, leading to seismic reflections[2]. These reflections are
then captured by strategically placed geophones or sensors, which convert ground vibrations into electrical signals for further analysis[7].
then captured by strategically placed geophones or sensors, which convert ground vibrations into electrical signals for further analysis[7].
The importance of reflection seismology in oil and gas exploration cannot be overstated. It plays a pivotal role in identifying potential hydrocarbon reservoirs, estimating hydrocarbon reserves, and assessing the viability of drilling projects[12].
By visualizing subsurface structures with high-quality details, oil and gas companies can make informed decisions about drilling and resource allocation, thereby reducing exploratory risks and increasing the chances of successful resource extraction[12].
Moreover, reflection seismology is cost-effective, time-efficient, and minimizes the environmental impact of drilling operations[12].
Specific Seismic Attributes and Wireline Log Data
New methods for the combined analysis of wireline logs, Vertical Seismic Profiles (VSPs), and prestack seismic data provide invaluable information about seismic velocities (P and S waves), anelastic attenuation (Q) factors, velocity anisotropy (of various symmetry axes), and multiples.
These datasets should be processed and analyzed together, reconciling differences due to the basic geophysics of the various measurements, the range of resolution scales, and different sources of errors and uncertainties, to achieve a unified and self-consistent borehole and surface-seismic
dataset[13].
dataset[13].
The processing of seismic data involves several steps to achieve an accurate earth image. The key processes include deconvolution, Common Midpoint (CMP) stacking, and migration. Normal moveout (NMO) correction, a part of CMP stacking, is performed using the primary velocity function. Multiples, which have larger moveout than primaries, are under-corrected and hence attenuated during stacking, improving the signal-to-noise ratio[6].
Additionally, dip-moveout correction preserves diffractions and fault-plane reflections, which can conflict with gently dipping reflections and are otherwise attenuated by conventional stacking[6].
Seismic waves generated during reflection seismic surveys propagate through geologic layers, with changes in physical properties such as density and seismic velocity occurring at the interfaces between different rock types. The resulting seismic records, which are sections or cubes of data with distance or geographic location on the horizontal axis and recording time on the vertical axis, provide critical information for subsurface imaging[2].
The selection of receiver equipment is equally important. Traditional geophone receivers connected with cables have been complemented by wireless seismic nodes, which offer several advantages for seismic acquisition[7]. The use of nuclear magnetic resonance (NMR) technology allows for the measurement of the relaxation characteristics of hydrogen-containing fluids in pores, providing detailed information on pore size, distribution, and fluid occurrence state in shale reservoirs[9].
Atomic force microscopy (AFM) technology further improves resolution, enabling detailed characterization of sample surface topography[9].
Collectively, these methods and technologies enhance the understanding of the subsurface, enabling the identification of the highest-productivity sweet spots in major shale gas plays by integrating seismic attributes and wireline log data.
Drilling Techniques
Advancements in drilling technologies have significantly improved the assessment and extraction of potential gas reserves, particularly in major shale gas plays.
Horizontal drilling and hydraulic fracturing, commonly known as fracking, are pivotal techniques in this domain. These methods enable the extraction of gas from otherwise hard-to-reach shale formations, maximizing the yield from a given well and providing valuable data about the shale layer’s characteristics, such as thickness and permeability[4].
The integration of seismic-to-simulation workflows with 3D reservoir models allows experts to identify and grade sweet spots early in the field development process based on reservoir quality and induced fracture permeability[10].
Seismic survey techniques are essential in exploring and assessing shale gas deposits. These methods use seismic waves, generated by small explosions or heavy machinery, to create images of subsurface geological formations. The reflected waves are detected by seismic receivers—microphones, geophones, hydrophones, or accelerometers—which convert them into electrical signals for processing. This processed data helps geologists identify potential gas-rich rock layers[2].
To optimize drilling and extraction, a comprehensive, calibrated workflow is necessary to account for factors such as matrix quality, natural fractures, and net gas porosity along laterals that can extend up to 5,000 feet. Production can vary significantly between wells, necessitating accurate ranking of potential drill locations, production performance prediction, and detailed planning of drilling and completion designs[10].
Additionally, advanced data analytics and modeling tools are employed to interpret the data collected from seismic surveys and drilling activities. This leads to better predictions regarding the viability and profitability of gas extraction projects.
By integrating various exploration datasets—seismic, well-log, petrophysical, and rock physics data—into a cohesive framework, the ambiguity in lead and prospect identification can be minimized[14]. These integrated solutions address the challenges of data integration in shale gas exploration, ensuring efficient and accurate evaluation of drillable shale prospects[14].
Advantages of Integrated Workflow
The implementation of an integrated seismic-to-simulation workflow offers numerous advantages in the identification of high-productivity sweet spots in shale gas plays. One of the primary benefits is the minimization of risk and uncertainty through the maintenance of consistency between the subsurface model and historical production data. This is achieved by relating simulation results to seismic data and vice versa, leading to more accurate business decisions[5].
The workflow incorporates early cross-domain consideration of scale and accurate velocity modeling, which helps to minimize upscaling ambiguities and resampling artifacts typically introduced in classical workflows. This attention to detail ensures that there is only marginal variation between results analyzed in time and depth, enhancing the fidelity of the analysis[5]. The a priori spatial grid sampling used in the workflow reduces overall inaccuracies, enabling more precise and rapid reservoir decision-making[5].
Moreover, the use of advanced inversion algorithms, such as the ISIS simultaneous inversion algorithm enhances the ability to predict key reservoir properties like acoustic impedance and Vp/Vs ratio[3]. These properties are crucial for determining reservoir quality and can be validated against well-log data, providing a robust framework for accurate interpretation and analysis[3].
Additionally, the integrated workflow is adaptable and can be incorporated into existing processes with ease. This flexibility is beneficial for operators looking to streamline their operations and improve efficiency without overhauling their entire system[5]. The process is agnostic to whether the data is time or depth-driven, adding
another layer of versatility to its application[5].
Finally, the adoption of lower-cost nodal seismic receiver technology as part of the workflow offers financial advantages. These nodes are becoming more accessible to smaller acquisition contractors, who can benefit from the reduced cash flow challenges and operational costs. This makes the technology not only economically viable but also environmentally friendly, as it requires less infrastructure and personnel[7].
However, some reluctance to adopt nodal technology still exists due to concerns about data reliability and other operational challenges[7].
Challenges and Limitations
In the domain of seismic surveys, one of the major challenges is the persistent use of outdated cable-based systems over newer nodal technologies. Many companies continue to rely on these older systems due to the lower costs associated with using existing, depreciated equipment as opposed to investing in new, economically unviable nodal systems[7].
Additionally, there is often a mindset of “don’t fix something that’s not broken” that further hinders the adoption of newer technologies[7]. The complexity of the terrain where seismic surveys are conducted also presents significant challenges. Scouting the environment and topography is crucial to understanding landscape logistics, operational efficiencies, and potential restrictions.
A thorough Scouting Report, inclusive of GIS Modelling, is essential to address these challenges, especially in areas with complex terrains where numerous unforeseen issues can arise[7]. Moreover, while 3D seismic methods provide improved image quality and greater data diversity, they are also more elaborate and costly compared to 2D methods.
The economics of the program, such as grid density, significantly impact the success of obtaining high-quality subsurface images. If detailed structural information is required, higher coverage is necessary, which increases costs. For example, in Western Canada, the comparison of 2D and 3D activities demonstrated that while 3D methods yield more optimized well locations and a better understanding of prospects, the daily costs and operational complexity are considerably higher[15].
Seismic data processing introduces another layer of complexity. The generation of numerical artifacts during signal enhancement can compromise the integrity of the data. Effective seismic data analysis programs need to minimize these artifacts to maintain data quality. The skill of the seismic data analyst is as crucial as the software’s effectiveness in determining the final product’s quality. Implementational differences in processing algorithms and the analyst’s proficiency can greatly influence the results, highlighting the necessity for both advanced software and skilled personnel[6].
Integrating seismic data with reservoir simulation results, though beneficial, presents its own set of limitations. Comprehensive data visualization and analytics software are needed to merge different datasets effectively. Without these tools, there is a risk of data loss and inefficiencies in decision-making. Streamlining data volumes and ensuring clear display of information is critical to reducing risks and optimizing the identification of profitable reservoir areas[16].
Future Trends
In the field of shale gas exploration, future trends are geared towards leveraging advanced technologies and innovative methodologies to improve efficiency and accuracy. One significant area of focus is the continued development and application of seismic technologies.
Seismic waves, traditionally used to study earthquakes, are now integral to oil and gas exploration. These waves, when sent deep into the Earth, provide geophysicists with valuable data on subterranean oil and gas reservoirs. This technology is not only beneficial for hydrocarbon extraction but is also being adapted for geothermal energy exploration and CO2 sequestration efforts[17].
Moreover, the integration of advanced data processing and visualization techniques will play a crucial role in future developments. For instance, 3-D seismic data processing enables detailed interpretation of subsurface structures, thus enhancing the identification of productive zones within shale gas plays. Tools like CoViz 4D offer comprehensive data visualization and analytics, enabling analysts to merge and scrutinize datasets from diverse disciplines. This leads to more informed decision-making and optimized exploration strategies[16].
Another promising trend is the utilization of remote sensing technologies, such as aerial surveys and satellite imagery. These techniques facilitate the initial identification of potential shale gas sites by analyzing surface characteristics indicative of underlying deposits. This approach helps in narrowing down vast search areas, making the exploration process more efficient[4].
Finally, the industry is witnessing a shift towards more environmentally sustainable practices. There is a growing demand for denser seismic surveys that are cost-effective and have a reduced environmental footprint. Deploying small, light autonomous nodes for seismic data acquisition is one such innovation. These nodes can be easily deployed across various terrains, allowing for superdense surveys and minimizing the environmental impact[7].
References
[1]: Oil and Gas Exploration Types of Seismic Surveys | Blog | Crown Exploration
[2]: The Defining Series: Beginner’s Guide to Seismic Surveying
[3]: An Integrated Workflow for Shale Gas in the Western Canadian …
[4]: How is the location of shale gas deposits determined?
[5]: Seismic Through Simulation With Integrated Time-Lapse Workflow
[6]: Processing of seismic data – SEG Wiki
[7]: A guide to land seismic survey design – Stryde
[8]: Seismic to Simulation: De-risking unconventional plays … – LinkedIn
[9]: Microstructure Characterization Techniques for Shale Reservoirs: A Review
[10]: Integrated Seismic-to-Simulation Workflow Identifies Highest …
[11]: Sweet spot identification – SEG Wiki
[12]: Unlocking Earth’s Secrets: The Role of Reflection Seismology in Oil and …
[13]: Well-driven seismic: 3D data processing solutions from wireline logs …
[14]: Integrated Seismic (IS) for Shale Gas Exploration and Management
[15]: THE VALUE OF 3D SEISMIC IN TODAY’S EXPLORATION ENVIRONMENT-Mustagh
[16]: Seismic Exploration: Understanding the Importance of Data Integration