Rock Physics Diagnostics Research Articles

Prediction of reservoir properties and fluids using rock physics techniques in the Rio Del Rey Basin, Cameroon

The application of rock physics modeling has been a breakthrough in oil and gas industry and has greatly managed exploration and interpretation risk. In the Rio del Rey Basin, the rock physics method was used to ascertain the reservoir's characteristics and relate them to the elastic characteristics. Using conventional techniques to connect to the elastic properties and assess various rock physics diagnostics, the estimated petrophysical parameters were water saturations, porosity, and shale volume. By connecting the saturated bulk modulus to its porosity, the bulk modulus of the porous frame, the bulk modulus of the mineral matrix, and the bulk modulus of the pore filling fluids, the Gassmann fluid replacement modeling was used to simulate various fluid scenarios. Finally, an evaluation was conducted on rock physics boundaries and cement models. The reservoirs are rated as extremely good based on the results. The rock physics model generated showed the friable sand model is a suitable model for the said basin and the rock physics bounds that were evaluated indicated that the sediments are deposited below the critical porosity and less compacted thereby depicting a soft sand model. Conventional petrophysical study would not be able to reveal the clustering of the gas sands from the brine sand and the shale zone in connection to the geologic trend as demonstrated by the rock physics template. The anticipated model will be useful to extrapolate the study to other sedimentary basins in Cameroon and estimate porosity from the impedance acquired from seismic data throughout the basin.

Rock physics and machine learning comparison: elastic properties prediction and scale dependency

Rock physics diagnostics (RPD) established based upon the well data are used to deterministically predict elastic properties of rocks from measured petrophysical rock parameters. However, with the recent advances in statistical methods, machine learning (ML) can help to build a shortcut between raw well data and rock properties of interest. Several studies have reported the comparison of rock physics and machine learning methods for the prediction of rock properties, but the scale dependence of the ML models was never investigated. This study aims at comparing the results from rock physics and machine learning models for predicting elastic properties such as bulk density (ρb), P-wave velocity (Vp), S-wave velocity (Vs), as well as Poisson’s ratio (v) and acoustic impedance (Ip) in a well from the Gulf of Mexico (GOM) in two different scale scenarios: the well log and seismic scales. The well data under examination was split into training and testing subsets to optimize and test the developed ML models. The RPD approach was also used to validate and compare the accuracy of predicted elastic properties. Backus averaging was later applied to upscale the well data to the seismic scale to examine the scale dependence and prediction accuracy of aforementioned physics-driven and data-driven approaches. Results show that RPD and ML methods provided consistent results at both well log and seismic scales, suggesting the scale independence of both approaches. Moreover, ML models showed better estimation of rock properties due to their “apparent” match with measured data at both scales compared to the RPD approach where a significant mismatch between measured and predicted rock properties was found in the reservoir section of the well. However, by conducting further quality control of the sonic data, it was found that the measured Poisson’s ratio was extremely high in the gas-saturated interval. Hence, the prediction from ML models in this particular case cannot be trusted as ML models were trained based on poor-quality well data with non-realistic Vs and v values. Such an issue, however, could be identified and corrected using RPD as presented in this study. We demonstrate the importance of incorporating domain knowledge, i.e., rock physics, to check data quality and validate results from data-driven models.

Rock physics modelling‐based characterization of deep and tight mixed sedimentary (clastic and carbonate) reservoirs: A case study from North Potwar Basin of Pakistan

AbstractRock physics modelling in deeply buried tight carbonate reservoirs is more challenging than the clastic reservoir because of its complex pore systems. Therefore, modelling complex pore geometries in carbonates reservoir plays an important role in the geophysical measurements to infer pore‐type distribution and their volume fraction, which control the fluid flow properties governed by their complex geological history. This paper presents the use of a robust and practical integrated and iterative seismic petrophysics, and rock physics modelling workflow for the characterization of a deep tight mixed (carbonate and clastic) sedimentary reservoir of a recently discovered oil field located in the Potwar Basin onshore Pakistan. The case study incorporates a careful assessment of well‐log data quality, workflow used for well data conditioning and consequent improvement in data quality, seismic petrophysics and rock physics modelling results. Rock physics diagnostics identified data quality issues and rectified them using appropriate measures to ensure that the rock physics modelling scheme reliably predicts elastic logs honouring different pore types (reference, soft, stiff and cracks) distribution validating from the well observations. Two inclusion‐based rock physics models (Xu and Payne for carbonate and Keys and Xu for clastic) are used to predict rock elastic (P‐sonic, S‐sonic and density) properties responses. Utmost care is exercised to integrate all available data/information, such as Formation Micro‐Imager, mud‐log, testing data and calibrated pore‐type inversion results from well‐log data with the pore geometry revealed by Formation Micro‐Imager and core information. The rock physics modelling provided consistency between elastic and petrophysical properties by calibrating the estimated properties with the measure logs and improved understanding in terms of lithology and fluid separation in the tight carbonate interval. Finally, rock physics‐modelled elastic logs (P‐sonic, S‐sonic and density) are used along with seismic data (partial stacks) and horizons interpretation model to compute pre‐stack synthetic seismograms to calibrate with the preconditioned seismic data. A significant improvement in the well‐to‐seismic calibration is achieved from rock physics modelled logs compared with the original (measured) elastic logs at well location using pre‐stack seismic data, which, further, can help produce reliable reservoir rock properties of interest from the inversion of seismic data.

Rock physics diagnostics and modelling of the Mangahewa Formation of the Maui B gas field, Taranaki Basin, offshore New Zealand

Rock physics diagnostics and modelling of the Mangahewa Formation of the Maui B gas field, Taranaki Basin, offshore New Zealand

Influence of Depositional and Diagenetic Processes on Caprock Properties of CO2 Storage Sites in the Northern North Sea, Offshore Norway

Characterization of caprock shale is critical in CO2 storage site evaluation because the caprock shale acts as a barrier for the injected buoyant CO2 plume. The properties of shales are complex and influenced by various processes; hence, it is challenging to evaluate the caprock quality. An integrated approach is therefore necessary for assessing seal integrity. In this study, we investigated the caprock properties of the Lower Jurassic Drake Formation shales from the proposed CO2 storage site Aurora (the Longship/Northern Lights CCS project), located in the Horda Platform area, offshore Norway. Wireline logs from 50 exploration wells, various 2D seismic lines, and two 3D seismic cubes were used to investigate the variations of the caprock properties. The Drake Formation was subdivided into upper and lower Drake units based on the lithological variations observed. Exhumation and thermal gradient influencing the caprock properties were also analyzed. Moreover, rock physics diagnostics were carried out, and caprock property maps were generated using the average log values to characterize the Drake Formation shales. In addiiton, pre-stack seismic-inverted properties and post-stack seismic attributes were assessed and compared to the wireline log-based analysis. The sediment source controlled at 61° N significantly influenced the depositional environment of the studied area, which later influenced the diagenetic processes and had various caprock properties. The upper and lower Drake units represent similar geomechanical properties in the Aurora area, irrespective of significant lithological variations. The Drake Formation caprock shale near the injection site shows less-ductile to less-brittle brittleness values. Based on the caprock thickness and shaliness in the Aurora injection site, Drake Formation shale might act as an effective top seal. However, the effect of injection-induced pressure changes on caprock integrity needs to be evaluated.

Rock Physics Model Provides Insight Into Reservoir Characterization

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 30359, “Reservoir Characterization Supported by Rock Physics Diagnostics,” by Stephan Gelinsky, Shell. The paper has not been peer reviewed. Copyright 2021 Offshore Technology Conference. Reproduced by permission. Rock physics models are often perceived as too complicated and dependent on too many difficult-to-measure parameters to be of practical use for reservoir characterization. In the complete paper, the author demonstrates how careful calibration of a common and simple rock physics model can provide valuable insights into the reservoir and seal elastic properties such as function of porosity, fluid, and mineral properties and net-to-gross. The model can be used for quantitative seismic interpretation of reservoirs with variable net-to-gross and porosity away from well control. Methodology Rock physics describes the application of fundamental physical principles to establish the elastic properties of porous rocks as a function of their mineral composition, pore fill, and microstructure and texture. Once a suitable rock physics model is calibrated locally, the use of seismic data to estimate reservoir rock and fluid properties from the elastic rock properties is possible—specifically, from the observed seismic amplitudes and if seismic data were inverted from the seismically derived acoustic and shear impedances. The Hashin-Shtrikman (HS) effective medium bounds can be used to characterize both sandstones and shales. While the application of this model for clean sandstones is straightforward and, thus, is not included in this synopsis, the application for shales is more complex.

Compaction, rock physics and rock properties of sandstones of the Stø Formation: Case study of five wells from the south-western Barents Sea, Norway

Five wells containing Lower-Middle Jurassic sandstones of Stø Formation from the Hammerfest Basin (7120/9–1, 7121/7–1), the Ringvassøy-Loppa Fault Complex (7119/12–1, 7119/12–4) and the Troms-Finnmark Fault Complex (7019/1-1) in the Barents Sea area are considered in this study. The Stø Formation sandstones contain dominantly very fine-to medium-grained quartz arenites with occasional coarse-grained sandstone layers. Feldspathic and quartz wackes are also present. The effect of compaction and exhumation on reservoir properties (porosity and permeability) and seismic property (P-wave velocity) of these sandstones have been investigated. Source of quartz cement has also been investigated. Forty polished thin sections embedded in blue epoxy were studied using optical microscopy, scanning electron microscopy and cathodoluminiscence. Bulk mineralogy was also analysed using X-ray diffraction.The studied sandstones have experienced Cenozoic exhumation ranging between 820 and 1050 m. P-wave velocity is higher; porosities and permeabilities are lower in the western wells (7019/1-1, 7119/12–1 and 7119/12–4) compared to the eastern wells (7120/9–1 and 7121/7–1). Rock physics models and diagnostics show that the western wells are diagenetically more mature, stiffer, more compacted and more cemented than the eastern wells. These trends are attributed largely to difference in burial history from the east to the west and less to textural variations. Quartz cement is the most important authigenic mineral in these sandstones. Quartz cement in the western well (7119/12–1) is predominantly derived from clay-induced dissolution at macrostylolites whereas the eastern wells (7120/9–1 and 7121/7–1) are mostly sourced from clay-induced dissolution at grain contacts or microstylolites. While cementational porosity loss dominates in the western wells, compactional porosity loss dominates in the eastern wells. Compaction can reduce porosities down to 26% and this might be the reason for better porosity preservation and reservoir quality in the eastern wells than in the western wells.

Reservoir assessment of Middle Jurassic sandstone-dominated formations in the Egersund Basin and Ling Depression, eastern Central North Sea

Abstract Reservoir quality assessment was conducted from petrophysical analysis and rock physics diagnostics on 15 wells penetrating Middle Jurassic sandstone reservoir formations in different regions of the eastern Central North Sea. Seismic interpretation on available 3D and 2D seismic reflection data was utilized to map thickness variations and to draw broad correlations to structural features such as salt structures and faults. In the central Egersund Basin, the Sandnes Formation shows good reservoir properties (gross thickness = 107–147 m, N/G = 33–53%) while the Bryne Formation exhibits poorer reservoir quality (N/G

Consolidating rock-physics classics: A practical take on granular effective medium models

Granular effective medium (GEM) models rely on the physics of a random packing of spheres. Although the relative simplicity of these models contrasts with the complex texture of most grain-based sedimentary rocks, their analytical form makes them easier to apply than numerical models designed to simulate more complex rock structures. Also, unlike empirical models, they do not rely on data acquired under specific physical conditions and can therefore be used to extrapolate beyond available observations. In addition to these practical considerations, the appeal of GEM models lies in their parameterization, which is suited for a quantitative description of the rock texture. As a result, they have significantly helped promote the use of rock physics in the context of seismic exploration for hydrocarbon resources by providing geoscientists with tools to infer rock composition and microstructure from sonic velocities. Over the years, several classic GEM models have emerged to address modeling needs for different rock types such as unconsolidated, cemented, and clay-rich sandstones. We describe how these rock-physics models, pivotal links between geology and seismic data, can be combined into extended models through the introduction of a few additional parameters (matrix stiffness index, cement cohesion coefficient, contact-cement fraction, and laminated clays fraction), each associated with a compositional or textural property of the rock. A variety of real data sets are used to illustrate how these parameters expand the realm of seismic rock-physics diagnostics by increasing the versatility of the extended models and facilitating the simulation of plausible geologic variations away from the wells.

Acoustic and petrophysical properties of mechanically compacted overconsolidated sands: Part 2 – Rock physics modelling and applications

ABSTRACTPart one of this paper reported results from experimental compaction measurements of unconsolidated natural sand samples with different mineralogical compositions and textures. The experimental setup was designed with several cycles of stress loading and unloading applied to the samples. The setup was aimed to simulate a stress condition where sediments underwent episodes of compaction, uplift and erosion. P‐wave and S‐wave velocities and corresponding petrophysical (porosity and density) properties were reported. In this second part of the paper, rock physics modelling utilizing existing rock physics models to evaluate the model validity for measured data from part one were presented. The results show that a friable sand model, which was established for normally compacted sediments is also capable of describing overconsolidated sediments. The velocity–porosity data plotted along the friable sand lines not only describe sorting deterioration, as has been traditionally explained by other studies, but also variations in pre‐consolidation stress or degree of stress release. The deviation of the overconsolidated sands away from the normal compaction trend on the VP/VS and acoustic impedance space shows that various stress paths can be predicted on this domain when utilizing rock physics templates. Fluid saturation sensitivity is found to be lower in overconsolidated sands compared to normally consolidated sands. The sensitivity decreases with increasing pre‐consolidation stress. This means detectability for four‐dimensional fluid saturation changes can be affected if sediments were pre‐stressed and unloaded. Well log data from the Barents Sea show similar patterns to the experimental sand data. The findings allow the development of better rock physics diagnostics of unloaded sediments, and the understanding of expected 4D seismic response during time‐lapse seismic monitoring of uplifted basins. The studied outcomes also reveal an insight into the friable sand model that its diagnostic value is not only for describing sorting microtextures, but also pre‐consolidation stress history. The outcome extends the model application for pre‐consolidation stress estimation, for any unconsolidated sands experiencing similar unloading stress conditions to this study.

Reservoir characterization of the Triassic Kobbe and Snadd formations — Bjarmeland Platform, Norwegian Barents Sea

A reservoir characterization study of the Triassic Kobbe and Snadd formations is carried out in the Bjarmeland Platform area, Norwegian Barents Sea, through detailed petrophysical analysis and rock physics diagnostics. Results are tied to depositional environments and discussed in the context of burial depth and cementation as present burial depth is less than maximum burial depth due to upliftment. Marginal marine sandstones in the Snadd Formation display marginally better reservoir quality on average than those of fluvial origin, yet higher quality individual reservoirs are observed within both facies. As expected, the Kobbe Formation reservoirs are consistently poorer. The sensitivity of existing rock physics models to the data is shown to be reasonably valid (via porosity, water saturation, shale volume). Snadd Formation reservoir sandstones not affected by cementation are only observed at shallow depth in the west of the study area. This is supported by comparison to an experimental compaction trend as well as rock physics models. All Kobbe Formation reservoir units show consistent signs of chemical compaction due to deeper burial. The main findings of this study are estimates of important reservoir properties and examples of how results from petrophysical analysis are validated and complemented in various rock physics domains.

Integrated facies modeling in unconventional reservoirs using a frequentist approach: Example from a South Texas field

Modeling of rock types or facies in unconventional reservoirs presents numerous challenges that are not encountered in conventional reservoirs. Because the exploitation of unconventional reservoirs frequently relies on the use of large numbers of long, data-poor horizontal wells, routine tasks in conventional reservoirs, such as petrophysical analyses and rock-physics diagnostics, become problematic in unconventional reservoirs due to insufficient data. Similarly, the inability to generate synthetic seismograms in the horizontal section of the wells makes seismic well ties and time-depth conversions more difficult. Our approach for facies modeling in unconventional reservoirs attempts to overcome these challenges by using the abundant log information available along the vertical pilot well to extract discrete facies indicators (facies flags) from logging-while-drilling information along the horizontals. After performing a time-depth conversion constrained by geosteering information, we estimate facies probabilities using facies flags and prestack elastic inversion results also extracted along the horizontals. As opposed to the Bayesian formalism commonly used for facies probabilities estimation, our frequentist approach estimates probabilities directly from proportions derived from crossplots of inverted elastic properties without using the Bayes formula. No prior information is required. The margin of error in the probabilities is also estimated by applying a well-known formula used to estimate the margin of error in opinion polls. Finally, we use seismic probability results to select only points with high probability and high reliability, which are treated as hard constraints for stochastic facies modeling. The selection of the seismic constraints is also weighted by the vertical facies trend expected for the area of interest. Our final facies model closely follows horizontal and vertical well facies data, vertical proportion curves, and selected seismic constraints. The application of the methodology is illustrated in a carbonate-rich, unconventional reservoir in South Texas.

Rock-physics diagnostics of an offshore gas field

Seismic reflections depend on the contrasts of the elastic properties of the subsurface and their 3D geometry. As a result, interpreting seismic data for petrophysical rock properties requires a theoretical rock-physics model that links the seismic response to a rock’s velocity and density. Such a model is based on controlled experiments in which the petrophysical and elastic rock properties are measured on the same samples, such as in the wellbore. Using data from three wells drilled through a clastic offshore gas reservoir, we establish a theoretical rock-physics model that quantitatively explains these data. The modeling is based on the assumption that only three minerals are present: quartz, clay, and feldspar. To have a single rock-physics transform to quantify the well data in the entire intervals under examination in all three wells, we introduced field-specific elastic moduli for the clay. We then used the model to correct the measured shear-wave velocity because it appeared to be unreasonably low. The resulting model-derived Poisson’s ratio is much smaller than the measured ratio, especially in the reservoir. The associated synthetic amplitude variation with offset response appears to be consistent with the recorded seismic angle stacks. We have shown how rock-physics modeling not only helps us to correct the well data, but also allows us to go beyond the settings represented in the wells and quantify the seismic signatures of rock properties and conditions varying in a wider range using forward seismic modeling.

Rock-physics diagnostics of a turbidite oil reservoir offshore northwest Australia

Interpreting seismic data for petrophysical rock properties requires a rock-physics model that links the petrophysical rock properties to the elastic properties, such as velocity and impedance. Such a model can only be established from controlled experiments in which both groups of rock properties are measured on the same samples. A prolific source of such data is wellbore measurements. We use data from four wells drilled through a clastic offshore oil reservoir to perform rock-physics diagnostics, i.e., to find a theoretical rock-physics model that quantitatively explains the measurements. Using the model, we correct questionable well curves. Moreover, a crucial purpose of rock-physics diagnostics is to go beyond the settings represented in the wells and understand the seismic signatures of rock properties varying in a wider range via forward seismic modeling. With this goal in mind, we use our model to generate synthetic seismic gathers from perturbational modeling to address “what-if” scenarios not present in the wells.

Porosity, mineralogy, and pore fluid from simultaneous impedance inversion

We find that in a quartz/clay system, P- and S-wave impedances (IP and IS, respectively) each uniquely depend on a different linear combination of the total porosity and clay content. This implies that if the pore fluid is known, we can resolve these two seismically derived impedances for porosity and clay content. Key to such interpretation is rock-physics diagnostics that provide a theoretical rock-physics model to quantitatively explain well data by relating IP and IS to porosity, clay content, and pore fluid. The well data conditioned according to this model serve as input to simultaneous impedance inversion. Poisson's or the IP/IS ratio serves as the pore-fluid identifier. We give an example of such rock-physics-based interpretation of seismically derived impedances for rock properties based on well and seismic data from an offshore oil field.

Rational Rock Physics for Improved Velocity Prediction and Reservoir Properties Estimation for Granite Wash (Tight Sands) in Anadarko Basin, Texas

Due to the complex nature, deriving elastic properties from seismic data for the prolific Granite Wash reservoir (Pennsylvanian age) in the western Anadarko Basin Wheeler County (Texas) is quite a challenge. In this paper, we used rock physics tool to describe the diagenesis and accurate estimation of seismic velocities of P and S waves in Granite Wash reservoir. Hertz-Mindlin and Cementation (Dvorkin’s) theories are applied to analyze the nature of the reservoir rocks (uncemented and cemented). In the implementation of rock physics diagnostics, three classical rock physics (empirical relations, Kuster-Toksöz, and Berryman) models are comparatively analyzed for velocity prediction taking into account the pore shape geometry. An empirical (VP-VS) relationship is also generated calibrated with core data for shear wave velocity prediction. Finally, we discussed the advantages of each rock physics model in detail. In addition, cross-plots of unconventional attributes help us in the clear separation of anomalous zone and lithologic properties of sand and shale facies over conventional attributes.

Rock-physics diagnostics of depositional texture, diagenetic alterations, and reservoir heterogeneity in high-porosity siliciclastic sediments and rocks — A review of selected models and suggested work flows

Rock physics has evolved to become a key tool of reservoir geophysics and an integral part of quantitative seismic interpretation. Rock-physics models adapted to site-specific deposition and compaction help extrapolate rock properties away from existing wells and, by so doing, facilitate early exploration and appraisal. Many rock-physics models are available, each having benefits and limitations. During early exploration or in frontier areas, direct use of empirical site-specific models may not help because such models have been created for areas with possibly different geologic settings. At the same time, more advanced physics-based models can be too uncertain because of poor constraints on the input parameters without well or laboratory data to adjust these parameters. A hybrid modeling approach has been applied to siliciclastic unconsolidated to moderately consolidated sediments. Specifically in sandstones, a physical-contact theory (such as the Hertz-Mindlin model) combined with theoretical elastic bounds (such as the Hashin-Shtrikman bounds) mimics the elastic signatures of porosity reduction associated with depositional sorting and diagenesis, including mechanical and chemical compaction. For soft shales, the seismic properties are quantified as a function of pore shape and occurrence of cracklike porosity with low aspect ratios. A work flow for upscaling interbedded sands and shales using Backus averaging follows the hybrid modeling of individual homogenous sand and shale layers. Different models can be included in site-specific rock-physics templates and used for quantitative interpretation of lithology, porosity, and pore fluids from well-log and seismic data.