Reservoir Solutions (RES)’s Post

𝗦𝗲𝗶𝘀𝗺𝗶𝗰 𝗔𝘁𝘁𝗿𝗶𝗯𝘂𝘁𝗲 𝗘𝘅𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗜𝗻 𝗣𝗲𝘁𝗿𝗼𝗹𝗲𝘂𝗺 𝗘𝘅𝗽𝗹𝗼𝗿𝗮𝘁𝗶𝗼𝗻 #Seismic attribute extraction is a technique that uses seismic data to generate quantitative measures of subsurface #geological features. It has become an essential tool in #hydrocarbon #exploration, as it provides detailed information about the #reservoir properties, which helps in the decision-making process. Seismic attributes are derived from seismic waves that are reflected from the subsurface layers. These attributes can be classified into several categories based on the physical properties they represent. Some common examples of seismic attributes include amplitude, frequency, phase, and coherence. One of the most important applications of seismic attribute extraction is in reservoir characterization. By analyzing the seismic attributes, geologists can understand the properties of the reservoir, such as porosity, permeability, and fluid saturation. This knowledge is crucial for optimizing the drilling and production operations, as it helps in identifying the most profitable locations for drilling. Seismic attributes are also used in seismic inversion, which is a technique used to convert seismic data into a quantitative description of the subsurface. Inversion algorithms use seismic attributes as input data to generate a model of the subsurface, which can be used to analyze the reservoir properties. Another application of seismic attributes is in seismic interpretation. By examining the seismic attributes, geologists can identify geological structures such as faults, fractures, and stratigraphic anomalies. This information is critical for understanding the overall geological framework of the area under exploration. Furthermore, seismic attribute extraction can be used to detect and map hydrocarbon indicators such as gas chimneys, oil slicks, and seismic velocity anomalies. By identifying these indicators, geologists can locate potential hydrocarbon reservoirs. In conclusion, seismic attribute extraction is an essential tool in petroleum exploration. It has transformed the way geologists analyze seismic data, providing a quantitative understanding of the subsurface. The variety of applications it offers has enabled the industry to make more informed decisions about where to drill and how to optimize production, ultimately leading to increased efficiency and profitability.

𝗦𝗲𝗶𝘀𝗺𝗶𝗰 𝗗𝗶𝗿𝗲𝗰𝘁 𝗛𝘆𝗱𝗿𝗼𝗰𝗮𝗿𝗯𝗼𝗻 𝗜𝗻𝗱𝗶𝗰𝗮𝘁𝗼𝗿 (𝗗𝗛𝗜): A seismic Direct Hydrocarbon Indicator (DHI) is a seismic attribute that indicates the presence of hydrocarbons (oil and gas) directly from seismic data. It is based on the principle that the presence of hydrocarbons can cause certain seismic responses that are different from those caused by water or other non-hydrocarbon substances. DHIs are useful in identifying potential hydrocarbon reservoirs, analyzing exploration prospects, and reducing drilling risks. There are several types of seismic DHIs that geoscientists commonly use: 1. Amplitude anomalies: DHIs based on amplitude anomalies are related to the contrasts in the seismic amplitudes caused by the presence of hydrocarbons. Hydrocarbons, being less dense than water or rocks, tend to reflect less seismic energy, resulting in low amplitudes. Common amplitude-based DHIs include bright spots (high amplitude anomalies), flat spots (constant amplitude), and dim spots (low amplitude anomalies). 2. AVO (amplitude-versus-offset) anomalies: AVO analysis involves analyzing the variations in seismic amplitudes as a function of offset or angle. Hydrocarbons can cause distinctive AVO anomalies, such as amplitude versus offset curves that deviate from the expected response for water or non-hydrocarbon-bearing rock layers. These anomalies can be indicators of potential hydrocarbon reservoirs. 3. Frequency anomalies: DHIs based on frequency anomalies are related to the changes in the seismic frequency spectrum caused by hydrocarbon-filled reservoirs. Hydrocarbon reservoirs often have lower seismic frequencies due to the attenuation of higher frequencies as seismic waves pass through the fluid-filled reservoir. 4. Velocity anomalies: Changes in seismic velocities can also be indicative of hydrocarbon presence. Hydrocarbons typically have lower seismic velocities than water or rocks, leading to velocity anomalies in seismic data. These anomalies can be observed as areas of abnormally low or high velocities. Seismic DHIs are interpreted and analyzed in conjunction with other geological and geophysical data to evaluate the potential for hydrocarbon accumulation. They can help geoscientists prioritize drilling locations, identify drilling targets, and make informed decisions during the exploration and development of oil and gas reservoirs. However, it is important to note that DHIs are not conclusive evidence of hydrocarbons and need to be further validated through additional data and analysis, such as well data, geological studies, and geophysical investigations. Photo Reference, Credit: https://lnkd.in/dTwsBHdB

𝗔𝗩𝗢 (𝗔𝗺𝗽𝗹𝗶𝘁𝘂𝗱𝗲 𝗩𝗮𝗿𝗶𝗮𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗢𝗳𝗳𝘀𝗲𝘁) ### Classification of AVO Responses AVO responses are typically classified into four main types (Class I to IV), based on their characteristic amplitude behavior with offset: 1. **Class I AVO**: Exhibits a high positive reflection coefficient at zero offset, which decreases with increasing offset. This response often indicates high-impedance contrasts, commonly associated with gas sands. 2. **Class II AVO**: Shows a reflection coefficient near zero at zero offset, which increases or decreases slightly with offset. These responses are more ambiguous but can suggest potential hydrocarbon presence. 3. **Class III AVO**: Characterized by a low or negative reflection coefficient at zero offset that becomes more negative with increasing offset. This is typically indicative of gas-charged sands with significant acoustic impedance contrast. 4. **Class IV AVO**: Displays a negative reflection coefficient at zero offset that becomes less negative or even positive with increasing offset. These responses are less common and can be associated with certain types of lithological variations. ### Application in Hydrocarbon Exploration AVO analysis is a crucial tool in hydrocarbon exploration for several reasons: 1. **Direct Hydrocarbon Indicators (DHIs)**: AVO can identify anomalies directly associated with the presence of hydrocarbons, such as bright spots or flat spots, which are strong indicators of gas or oil. 2. **Reservoir Characterization**: By analyzing AVO responses, geophysicists can estimate the properties of the reservoir rocks, including porosity and fluid saturation, which are vital for assessing the quality and quantity of the hydrocarbon reserves. 3. **Risk Reduction**: AVO analysis helps in reducing exploration risk by providing more accurate predictions of subsurface conditions. This leads to more informed decision-making and optimizes drilling targets. 4. **Enhanced Seismic Interpretation**: Integrating AVO analysis with other geophysical data enhances the overall interpretation of seismic surveys, providing a more comprehensive understanding of the subsurface geology. Photo refrence, credit : https://lnkd.in/dZTKiqni

𝗦𝗵𝗲𝗮𝗿 𝗩𝗲𝗹𝗼𝗰𝗶𝘁𝘆 𝗜𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 #### Understanding Shear Waves and Velocity Inversion Seismic waves, generated during exploration surveys, come in two primary forms: compressional (P-waves) and shear (S-waves). While P-waves travel through both solid and fluid media, S-waves propagate only through solids, making them particularly useful for studying rock properties. The speed at which these waves travel—shear velocity—depends on the density and elastic properties of the subsurface materials. Shear velocity inversion refers to the process of deducing subsurface properties by interpreting the variations in shear wave velocities recorded during seismic surveys. This technique involves inverting the seismic data to produce a model that describes the velocity distribution in the subsurface. #### Applications in Petroleum Exploration 1. **Reservoir Characterization**: Shear velocity inversion is crucial for identifying lithology and fluid content in reservoirs. By distinguishing between different rock types and fluid saturations, geophysicists can infer the presence of hydrocarbons. For instance, gas-bearing formations often exhibit lower shear velocities compared to water-bearing formations due to the difference in compressibility. 2. **Fracture Detection**: In unconventional reservoirs, such as shale plays, the identification and characterization of fractures are essential for efficient hydrocarbon extraction. Shear wave data, through inversion techniques, help in mapping fracture networks and assessing their orientations and densities, which directly influence the permeability and productivity of the reservoir. 3. **Elastic Properties Estimation**: Shear velocity inversion aids in estimating key elastic properties of subsurface formations, such as Young's modulus and Poisson's ratio. These properties are integral to understanding the mechanical behavior of the reservoir rocks, which impacts drilling safety and well stability. 4. **Anisotropy Analysis**: The earth's subsurface is often anisotropic, meaning its properties vary with direction. Shear waves are sensitive to these variations, and inversion techniques can reveal anisotropic characteristics, providing insights into stress fields and helping to optimize drilling directions to avoid hazards and maximize hydrocarbon recovery. Photo refrence, credit : https://lnkd.in/dsNDrdwu

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𝗣𝗲𝘁𝗿𝗼𝗹𝗲𝘂𝗺 𝗘𝘅𝗽𝗹𝗼𝗿𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 ### 1. Geological and Geophysical Studies: - **Basin Analysis**: Geologists study sedimentary basins to understand their geological history, tectonic evolution, and depositional environments. - **Seismic Surveys**: Geophysicists use seismic reflection surveys to create detailed images of subsurface rock formations. - **Gravity and Magnetic Surveys**: Gravity and magnetic surveys help map subsurface rock properties and structures, providing additional insights into potential hydrocarbon-bearing formations. ### 2. Prospect Identification: - **Play Concept Development**: Geoscientists develop play concepts based on geological and geophysical data, outlining potential hydrocarbon traps, reservoir rocks, and source rocks within a specific exploration area. - **Prospect Generation**: Prospects are specific exploration targets identified within plays based on favorable geological and geophysical characteristics. ### 3. Exploration Drilling: - **Exploratory Drilling**: Once prospects are identified, exploratory wells are drilled to test for the presence of hydrocarbons. Well logging, coring, and fluid sampling are used to evaluate reservoir properties, hydrocarbon content, and fluid characteristics. - **Wildcat Wells**: Wildcat wells are drilled in unexplored or frontier areas where little or no geological data exist. They carry higher risk but offer the potential for significant discoveries. ### 4. Reservoir Evaluation: - **Reservoir Characterization**: Successful exploration wells undergo detailed reservoir characterization to assess reservoir quality, connectivity, and producibility. - **Resource Estimation**: Geoscientists and engineers estimate the size, extent, and recoverable volumes of discovered hydrocarbon accumulations using reservoir modeling and simulation techniques. ### 5. Economic Analysis: - **Cost-Benefit Analysis**: Petroleum companies conduct economic evaluations to assess the viability of discovered reserves based on factors such as production costs, oil and gas prices, tax regimes, and project economics. - **Risk Assessment**: Exploration risks, including geological, technical, operational, and market risks, are evaluated to determine the overall investment attractiveness of exploration projects. ### 6. Development and Production: - **Field Development**: If a discovery is deemed commercially viable, it undergoes field development planning to optimize well placement, production techniques, and infrastructure design. - **Production Operations**: Once production begins, petroleum engineers oversee the operation of wells, facilities, and infrastructure to extract and process hydrocarbons efficiently and safely. Photo refrence, credit : https://lnkd.in/dRFXtQdp

* Using seismic velocity to derisk oil exploration: https://lnkd.in/d2eWwH9D An effective approach for early identification of oil in a prospect, based on initial water saturation values calculated from seismic velocities, Martin Essenfeld and Rafael Sandrea, July 15, 2024. In a recent GEO EXPRO article, we developed a field-based approach to identify natural gas prospects directly from seismic surveys. The gas fields are straight up. If the p-wave velocities (Vp) calculated from the seismic are below 11,000 ft/s, gas is the option. Reservoir fluid saturated rock Vp values greater than this gas threshold indicate liquids, oil or water, both of which have similar Vp values. The explorationist’s enigma is how to distinguish the ones that contain oil. The purpose of this study is to develop a method that could identify an oil prospect directly from the seismic. Our approach is to determine the rock’s water saturation by analyzing the behaviour of 20 major oil fields around the world. Water saturation is an important reservoir parameter that determines reserves and well productivities. Morris and Biggs (1967) developed the following proven equation that relates permeability (k), porosity (Ø) and irreducible water saturation in sandstones.

𝗗𝗶𝗿𝗲𝗰𝘁 𝗛𝘆𝗱𝗿𝗼𝗰𝗮𝗿𝗯𝗼𝗻 𝗜𝗻𝗱𝗶𝗰𝗮𝘁𝗼𝗿 𝗗𝗛𝗜 Direct Hydrocarbon Indicators (DHIs) are geological, geophysical, or geochemical anomalies that directly indicate the presence of hydrocarbons in a reservoir. These indicators are used in the exploration and assessment of hydrocarbon resources and can provide valuable information about the potential presence and distribution of oil and gas. DHIs are identified through various methods, including seismic interpretation, well logging, and geochemical analysis. Some common types of DHIs include: 1. Amplitude anomalies: These are variations in seismic amplitudes that suggest the presence of hydrocarbons. They can include bright spots (high amplitude) or dim spots (low amplitude) relative to the surrounding rock formations. 2. Flat spots: These are seismic reflections that appear flat, indicating the presence of a hydrocarbon-water contact. The change in acoustic impedance between hydrocarbons and water can create a distinct reflector that appears as a flat spot on seismic data. 3. Chimneys and fluid escape features: These are geological features that indicate the migration and escape of hydrocarbons through the rock layers, leaving behind distinct pathways and anomalies. 4. Seismic response anomalies: Variations in seismic wave propagation caused by the presence of hydrocarbons can create anomalies, such as amplitude versus offset (AVO) anomalies or frequency enhancements, that can be indicative of hydrocarbon presence. 5. Geochemical indicators: Geochemical analyses of rock samples, fluids, and gases can provide direct evidence of the presence of hydrocarbons, such as the presence of oil or gas biomarkers, isotopic signatures, or geochemical anomalies. The identification and interpretation of DHIs are critical for the assessment of exploration prospects, reservoir characterization, and well planning in the oil and gas industry. By recognizing and understanding these indicators, geoscientists and petroleum engineers can make informed decisions about drilling locations, reservoir potential, and the presence of commercial hydrocarbon accumulations. Overall, DHIs play a crucial role in reducing exploration risk and optimizing hydrocarbon discovery and recovery. Photo Reference, Credit: https://lnkd.in/dMvVvRTn Contact Us: Mail: Reservoir.Solutions.Egypt@gmail.com Website: https://lnkd.in/dZxwZJJk WhatsApp: +201093323215

𝗦𝗲𝗶𝘀𝗺𝗶𝗰 𝗪𝗲𝗹𝗹-𝗧𝗶𝗲 𝗣𝗿𝗼𝗰𝗲𝘀𝘀 The seismic well-tie process is a crucial step in the oil and gas exploration and production workflow. It involves integrating well data such as logs, well tops, and core data with seismic data to establish a correlation between the geological features identified in the well and those interpreted from the seismic data. This process is essential for accurately understanding subsurface geology and for making informed decisions about drilling and production strategies. The seismic well-tie process begins with the collection of seismic data using various techniques such as reflection seismology. Seismic data provides images of the subsurface by measuring the time it takes for sound waves to travel through the Earth and reflect back to the surface. These data are then processed to create seismic images that represent the subsurface geological structures and potential hydrocarbon reservoirs. Simultaneously, well data is collected from actual boreholes drilled into the subsurface. This includes logging data, which provides information about the rock properties, such as porosity and lithology, and core samples which can be analyzed to further understand the geological formations. The next step in the seismic well-tie process involves the interpretation of the seismic data to identify subsurface features such as faults, folds, and potential hydrocarbon-bearing formations. This interpretation is then correlated with the well data to establish a connection between the subsurface structures identified in both datasets. One of the key challenges in the seismic well-tie process is aligning the two datasets, as they are obtained using different measurement methods and have different resolutions. Seismic data typically covers a large area with lower resolution, while well data provides detailed and precise information from localized points. To overcome this challenge, geoscientists use various techniques, such as synthetic seismograms, which are artificial seismic traces generated from the well log data. These synthetic seismograms are then compared to the actual seismic data, allowing for adjustments to be made to the depth and time of the seismic reflections, creating a tie between the well data and the seismic data. The accuracy of the seismic well-tie is critical for making informed decisions in exploration and production activities, such as well placement, reservoir characterization, and production optimization. An accurate tie ensures that the subsurface structures identified in the seismic data are correctly correlated with the geological formations encountered in the wells, providing a reliable basis for understanding the reservoir architecture and potential hydrocarbon accumulation. Photo Reference, Credit: https://lnkd.in/efZGfiQE

* Seismic velocity – A strong identifier of gas prospects: https://lnkd.in/drFSX5_Q Using a dataset of major oil and gas fields across the globe, the authors demonstrate that Vp is a powerful tool to differentiate between oil and gas-filled traps, which helps de-risk future drilling targets. Using a dataset of major oil and gas fields across the globe, the authors demonstrate that Vp is a powerful tool to differentiate between oil and gas-filled traps, which helps de-risk future drilling targets. P-wave velocity (Vp) is an essential parameter for constructing seismic velocity models for geophysical exploration data, and porosity is the single most important factor affecting it, along with the type of pore fluids. Until recently, seismic velocity was only used for migrating seismic data and time-depth conversion. However, with recent new technologies like Full Waveform Inversion (FWI), the accuracy of the velocity data has improved. This advance now should provide an opportunity to estimate dependable key reservoir characteristics and at the same time detect any gas traps or accumulations from the seismic survey. Here, we focus on analysing Vp to identify gas accumulations during the early exploration phase, prior to spudding the first well, when only seismic data is available. One of the driving forces for this project was the consideration of the future role of natural gas in a global context. For this analysis, our approach was to analyse field seismic data, in particular Vp values, from randomly selected conventional gas fields around the world. We used P-wave velocity data available in the public domain and referred to as the velocity over the whole sedimentary hydrocarbon interval of the field. We looked at 32 oil and gas fields from 16 countries; most are giants, and the others are qualitatively world-class (Table 1).