New Workflow in Reservoir Modelling - Incorporating High Resolution Seismic and Rock Physics

2018 ◽  
Author(s):  
Deva Ghosh ◽  
Amir Babasafari ◽  
Teresa Ratnam ◽  
Chico Sambo
Keyword(s):  
High Resolution ◽  
Rock Physics ◽  
Reservoir Modelling

Geostatistical Inversion in Carbonate Reservoirs to Map Reservoir Quality With High Predictability – A Case Study From Onshore Abu Dhabi

2021 ◽  
Author(s):  
S Al Naqbi ◽  
J Ahmed ◽  
J Vargas Rios ◽  
Y Utami ◽  
A Elila ◽  
...  
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Pore Volume ◽  
Rock Physics ◽  
Static Model ◽  
Reservoir Quality ◽  
Reservoir Properties ◽  
Geostatistical Inversion ◽  
High Predictability ◽  
The Impact

Abstract The Thamama group of reservoirs consist of porous carbonates laminated with tight carbonates, with pronounced lateral heterogeneities in porosity, permeability, and reservoir thickness. The main objective of our study was mapping variations and reservoir quality prediction away from well control. As the reservoirs were thin and beyond seismic resolution, it was vital that the facies and porosity be mapped in high resolution, with a high predictability, for successful placement of horizontal wells for future development of the field. We established a unified workflow of geostatistical inversion and rock physics to characterize the reservoirs. Geostatistical inversion was run in static models that were converted from depth to time domain. A robust two-way velocity model was built to map the depth grid and its zones on the time seismic data. This ensured correct placement of the predicted high-resolution elastic attributes in the depth static model. Rock physics modeling and Bayesian classification were used to convert the elastic properties into porosity and lithology (static rock-type (SRT)), which were validated in blind wells and used to rank the multiple realizations. In the geostatistical pre-stack inversion, the elastic property prediction was constrained by the seismic data and controlled by variograms, probability distributions and a guide model. The deterministic inversion was used as a guide or prior model and served as a laterally varying mean. Initially, unconstrained inversion was tested by keeping all wells as blind and the predictions were optimized by updating the input parameters. The stochastic inversion results were also frequency filtered in several frequency bands, to understand the impact of seismic data and variograms on the prediction. Finally, 30 wells were used as input, to generate 80 realizations of P-impedance, S-impedance, Vp/Vs, and density. After converting back to depth, 30 additional blind wells were used to validate the predicted porosity, with a high correlation of more than 0.8. The realizations were ranked based on the porosity predictability in blind wells combined with the pore volume histograms. Realizations with high predictability and close to the P10, P50 and P90 cases (of pore volume) were selected for further use. Based on the rock physics analysis, the predicted lithology classes were associated with the geological rock-types (SRT) for incorporation in the static model. The study presents an innovative approach to successfully integrate geostatistical inversion and rock physics with static modeling. This workflow will generate seismically constrained high-resolution reservoir properties for thin reservoirs, such as porosity and lithology, which are seamlessly mapped in the depth domain for optimized development of the field. It will also account for the uncertainties in the reservoir model through the generation of multiple equiprobable realizations or scenarios.

Digital rock physics and application of high-resolution micro-CT techniques for geomaterials

2018 ◽  
pp. 299-307 ◽  
Author(s):  
Bankim Mahanta ◽  
P.G. Ranjith ◽  
T.N. Singh ◽  
Vikram Vishal ◽  
WenHui Duan ◽  
...  
Keyword(s):  
High Resolution ◽  
Rock Physics ◽  
Micro Ct ◽  
Digital Rock Physics ◽  
Digital Rock

Joint receiver function and gravity inversion for new constraints on the Ivrea body structure: a 2D high-resolution view along the Val Sesia profile (N. Italy).

2021 ◽  
Author(s):  
Matteo Scarponi ◽  
György Hetényi ◽  
Jaroslava Plomerová ◽  
Stefano Solarino
Keyword(s):  
High Resolution ◽  
Velocity Structure ◽  
Receiver Function ◽  
Joint Inversion ◽  
Gravity Data ◽  
Rock Physics ◽  
Receiver Functions ◽  
Gravity Inversion ◽  
European Alps ◽  
Horizontal Distance

<p>We present results from a joint inversion study of new seismic and gravity data to constrain a 2D high-resolution image of one of the most prominent geophysical anomalies of the European Alps: the Ivrea geophysical body (IGB). Our work exploits both new data and multidisciplinary a priori constraints, to better resolve the shallow crustal structure in the Ivrea-Verbano zone (IVZ), where the IGB is known to reach anomalously shallow depths and partially outcrop at the surface.</p><p>A variety of previous studies, ranging from gravity surveys to vintage refraction seismics and recent local earthquake tomographies (Solarino et al. 2018, Diehl et al. 2009), provide comprehensive but spatially sparse information on the IGB structure, which we aim at investigating at higher resolution, along a linear profile crossing the IVZ. To this purpose, we deployed 10 broadband seismic stations (MOBNET pool, IG CAS Prague), 5 km spaced along a linear West-East profile, along Val Sesia and crossing Lago Maggiore. This network operated for 27 months and allowed us to produce a new database of ca. 1000 seismic high-quality receiver functions (RFs). In addition, we collected new gravity data in the IVZ, with a data coverage of 1 gravity point every 1-2 km along the seismic profile. The newly collected data was used to set up an inversion scheme, in which RFs and gravity anomalies are jointly used to constrain the shape and the physical property contrasts across the IGB interface.</p><p>We model the IGB as a single interface between far-field constraints, whose geometry is defined by the coordinates of four nodes which may vary in space, and  density and V<sub>S</sub> shear-wave velocity contrasts associated with the interface itself, varying independently. A Markov chain Monte Carlo (MCMC) sampling method with Metropolis-Hastings selection rule was implemented to efficiently explore the model space, directing the search towards better fitting areas.</p><p>For each model, we perform ray-tracing and RFs migration using the actual velocity structure both for migration and computation of synthetic RFs, to be compared with the observations via cross-correlation of the migration images. Similarly, forward gravity modelling for a 2D density distribution is implemented and the synthetic gravity anomaly is compared with the observations along the profile. The joint inversion performance is the product of these two misfits.</p><p>The inversion results show that the IGB reaches the shallowest depths in the western part of the profile, preferentially locating the IGB interface between 3 and 7 km depth over a horizontal distance of ca. 20 km (between Boccioleto and Civiasco, longitudes 8.1 and 8.3). Within this segment, the shallowest point reaches up to 1 km below sea level. The found density and velocity contrasts are in agreement with rock physics properties of various units observed in the field and characterized in earlier studies.</p>

Reservoir modelling based on 3D high-resolution seismic data

2017 ◽  
Author(s):  
Chen Xin ◽  
Wei Xiao-dong ◽  
Li Yan-jing ◽  
Yan Xiao-huan ◽  
Xia Yaliang
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Reservoir Modelling

Seismic monitoring of a CO2 flood in a carbonate reservoir: A rock physics study

Geophysics ◽  
1998 ◽  
Vol 63 (5) ◽  
pp. 1604-1617 ◽  
Author(s):  
Zhijing Wang ◽  
Michael E. Cates ◽  
Robert T. Langan
Keyword(s):  
High Resolution ◽  
Pore Pressure ◽  
Rock Physics ◽  
Fluid Substitution ◽  
High Porosity ◽  
High Permeability ◽  
Pressure Buildup ◽  
Reservoir Rocks ◽  
Velocity Changes

A carbon dioxide (CO2) injection pilot project is underway in Section 205 of the McElroy field, West Texas. High‐resolution crosswell seismic imaging surveys were conducted before and after CO2 flooding to monitor the CO2 flood process and map the flooded zones. The velocity changes observed by these time‐lapse surveys are typically on the order of −6%, with maximum values on the order of −10% in the vicinity of the injection well. These values generally agree with laboratory measurements if the effects of changing pore pressure are included. The observed dramatic compressional ([Formula: see text]) and shear ([Formula: see text]) velocity changes are considerably greater than we had initially predicted using the Gassmann (1951) fluid substitution analysis (Nolen‐Hoeksema et al., 1995) because we had assumed reservoir pressure would not change from survey to survey. However, the post‐CO2 reservoir pore fluid pressure was substantially higher than the original pore pressure. In addition, our original petrophysical data for dry and brine‐saturated reservoir rocks did not cover the range of pressures actually seen in the field. Therefore, we undertook a rock physics study of CO2 flooding in the laboratory, under the simulated McElroy pressures and temperature. Our results show that the combined effects of pore pressure buildup and fluid substitution caused by CO2 flooding make it petrophysically feasible to monitor the CO2 flood process and to map the flooded zones seismically. The measured data show that [Formula: see text] decreases from a minimum 3.0% to as high as 10.9%, while [Formula: see text] decreases from 3.3% to 9.5% as the reservoir rocks are flooded with CO2 under in‐situ conditions. Such [Formula: see text] and [Formula: see text] decreases, even if averaged over all the samples measured, are probably detectable by either crosswell or high‐resolution surface seismic imaging technologies. Our results show [Formula: see text] is sensitive to both the CO2 saturation and the pore pressure increase, but [Formula: see text] is particularly sensitive to the pore pressure increase. As a result, the combined [Formula: see text] and [Formula: see text] changes caused by the CO2 injection may be used, at least semiquantitatively, to separate CO2‐flooded zones with pore pressure buildup from those regions without pore pressure buildup or to separate CO2 zones from pressured‐up, non‐CO2 zones. Our laboratory results show that the largest [Formula: see text] and [Formula: see text] changes caused by CO2 injection are associated with high‐porosity, high‐permeability rocks. In other words, CO2 flooding and pore pressure buildup decrease [Formula: see text] and [Formula: see text] more in high‐porosity, high‐permeability samples. Therefore, it may be possible to delineate such high‐porosity, high‐permeability streaks seismically in situ. If the streaks are thick enough compared to seismic resolution, they can be identified by the larger [Formula: see text] or [Formula: see text] changes.

3D rock minerals by correlating XRM and automated mineralogy and its application to digital rock physics for elastic properties

Geophysics ◽  
2021 ◽  
pp. 1-76
Author(s):  
Jin Hao ◽  
Guoliang Li ◽  
Jiao Su ◽  
Yuan Yuan ◽  
Zhongming Du ◽  
...  
Keyword(s):  
High Resolution ◽  
Elastic Properties ◽  
Rock Physics ◽  
Large Field ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
Mineral Phases ◽  
Rock Structure ◽  
Shale Sample ◽  
Automated Mineralogy

Digital rock physics (DRP) is an emerging technique that has rapidly become an indispensable tool to estimate elastic properties. The success of DRP mainly depends on three factors: acquiring a 3D rock structure image, accurately identifying 3D minerals, and using a proper numerical simulation method. Shales present a substantial challenge for DRP owing to their heterogeneous structure, composition, and properties from micron to centimeter scale. To obtain a sufficiently large field-of-view (FOV) image of a sample that reflects the detailed and representative internal structure and composition, we have developed a new DRP workflow to obtain large-FOV high-resolution digital rocks with 3D mineralogical information. Using the “divide-and-stitch” technique, a long shale sample is divided into several subunits, imaged separately by high-resolution X-ray microscopy (XRM), and then stitched to obtain a large-FOV 3D digital rock. An FOV of a rock cylinder (736 μm in diameter, 2358 μm in height, and 1 μm resolution) is used as an example. By correlating XRM and automated mineralogy, a large-FOV 3D mineral digital rock is obtained from a shale sample. Six mineral phases are identified and verified by automated mineralogy, and four laminae are detected according to the grain size, which offer a new perspective to study sedimentary processes and heterogeneities at the millimeter scale. The finite-difference method is used to compute the elastic properties of the large-FOV 3D mineral digital rock, and the results of Young’s modulus are within the limit of the Voigt/Reuss bounds. It also reveals that there is a difference in simulated elastic properties in the four laminae. The large-FOV 3D mineral digital rock offers the potential to explore the relationship between elastic properties and mineral phases, as well as the heterogeneities of elastic properties at the millimeter scale.

Digital rock physics: Segmentation of sub-resolution features

2020 ◽  
Author(s):  
Martin Balcewicz ◽  
Erik H. Saenger
Keyword(s):  
Computed Tomography ◽  
High Resolution ◽  
Rock Physics ◽  
Rock Properties ◽  
X Ray ◽  
Digital Rock Physics ◽  
Tomography Image ◽  
X Ray Computed ◽  
Computed Tomography Image ◽  
Elastic Rock

<p>Digital rock physics (DRP) became a complementary part in reservoir characterization during the last two decades. Deriving transport, thermal, or effective elastic rock properties from a digital twin requires a three-step workflow: (1) Preparation of a high-resolution X-ray computed tomography image, (2) segmentation of pore and grain phases, respectively, and (3) solving equations due to the demanded properties. Despite the high resolution µ-CT images, the numerical predictions of rock properties have their specific uncertainties compared to laboratory measurements. Missing unresolved features in the µ-CT image might be the key issue. These findings indicate the importance of a full understanding of the rocks microfabrics. Most digital models used in DRP treat the rock as a heterogeneous, isotropic, intact medium which neglect unresolved features. However, we expect features within the microfabrics like micro-cracks, small-scale fluid inclusions, or stressed grains which may influence the elastic rock properties but have not been taken into account in DRP, yet. Former studies have shown resolution-issues in grain-to-grain contacts within sandstones or inaccuracies due to micro-porosity in carbonates, this means the micritic phase. Within the scope of this abstract, we image two different sandstone samples, Bentheim and Ruhrsandstone, as well as one carbonate sample. Here, we compare the mentioned difficulties of X-ray visualization with further analytical methods, this means thin section and focused ion beam measurements. This results into a better understanding of the rocks microstructures and allows us to segment unresolved features in the X-ray computed tomography image. Those features can be described with effective properties at the µ-scale in the DRP workflow to reduce the uncertainty of the predicted rock properties at the meso- and fieldscale.</p>

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