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.

scholarly journals Deep Learning a Poro-Elastic Rock Physics Model for Pressure and Saturation Discrimination

Geophysics ◽  
2020 ◽  
pp. 1-55
Author(s):  
Wolfgang Weinzierl ◽  
Bernd Wiese
Keyword(s):  
Pore Pressure ◽  
Co2 Storage ◽  
Rock Physics ◽  
Seismic Attenuation ◽  
Physical Models ◽  
Physical Parameters ◽  
High Porosity ◽  
Hydrocarbon Production ◽  
Physical Attributes ◽  
Physics Model

Determining saturation and pore pressure is relevant for hydrocarbon production as well as natural gas and CO2 storage. In this context seismic methods provide spatially distributed data used to determine gas and fluid migration. A method is developed that allows to determine saturation and reservoir pressure from seismic data, more precisely from rock physical attributes that are velocity, attenuation and density. Two rock physical models based on Hertz-Mindlin-Gassmann and Biot-Gassmann are developed. Both generate poroelastic attributes from pore pressure, gas saturation and other rock-physical parameters. The rock physical models are inverted with deep neural networks to derive e.g. saturation, pore pressure and porosity from rock physical attributes. The method is demonstrated with a 65 m deep unconsolidated high porosity reservoir at the Svelvik ridge, Norway. Tests for the most suitable structure of the neural network are carried out. Saturation and pressure can be meaningfully determined under condition of a gas-free baseline with known pressure and data from an accurate seismic campaign, preferably cross-well seismic. Including seismic attenuation increases the accuracy. The training requires hours, predictions just a few seconds, allowing for rapid interpretation of seismic results.

Pay Zone Protection During Drilling In Offshore Oilfield Producing With High Porosity, High Permeability And Low Pore Pressure

2010 ◽  
Author(s):  
Wei Jiang ◽  
Jianming Deng ◽  
Xiaocheng Zhang ◽  
Wenbo Tang ◽  
Zili Li ◽  
...  
Keyword(s):  
Pore Pressure ◽  
High Porosity ◽  
High Permeability

scholarly journals AVO Analysis of a Weak BSR on the Hikurangi Margin, New Zealand

2021 ◽  
Author(s):  
◽  
Srinivasan Navalpakam Roopa
Keyword(s):  
New Zealand ◽  
Reflection Coefficient ◽  
Gas Hydrate ◽  
Rock Physics ◽  
High Amplitude ◽  
Low Permeability ◽  
High Permeability ◽  
Reservoir Rocks ◽  
Avo Analysis ◽  
Hydrate Stability

<p><b>Gas hydrates occur in deep, cold areas on the Hikurangi margin, New Zealand, generally at water depths of ≥ 600m and ≤ 8oC temperature. In these areas elevated hydrostatic pressures and low temperatures create stable conditions for hydrate formation. The occurrence of Bottom-Simulating Reflections (BSRs) is known to indicate the Base of the Gas Hydrate Stability (BGHS) zone, below which solid hydrates cannot exist due to increasing temperatures of sediments. BSRs in most settings worldwide are thought to be largely caused by free gas at the base of the gas hydrate stability zone. They are characterized by a large negative reflection coefficient due to significant decrease in P-wave velocity attributed to the presence of gas below the BSR. On the Hikurangi margin however, many BSRs appear relatively weak. This study presents the results of Amplitude Variation with Offset (AVO) analysis of a weak BSR beneath Puke Ridge, a thrust ridge on the accretionary wedge east of Gisborne, North Island. Rock-physics modelling is used to interpret the findings.</b></p> <p>The 05CM04 seismic line has been processed by preserving the amplitude and care has been taken to not bias the variation of reflectivity coefficient with offset. The zero-offset reflection coefficient or AVO intercept (A) is in the range of -0.008 to - 0.015 and the AVO gradient (B) is between -0.015 and -0.03.</p> <p>Rock-physics modelling was employed to determine the possible concentrations of gas and hydrate that can yield the observed reflection coefficients. Negligible hydrate saturation above with a patchy gas distribution of 3% saturation beneath the BSR might explain this pattern. An alternative end-member estimation of 13% saturation of hydrate in a frame-supporting model with no gas beneath it could generate the observed reflection coefficient but it is geologically unlikely. Synthetic modelling reveals that the low reflectivity of the BSR could also be due to the presence of thin layers of more concentrated or evenly distributed gas but this scenario is considered to be geologically unlikely.</p> <p>BSRs beneath some thrust ridges in the southern Hikurangi margin, appear as a series of clearly separated bright spots, which indicate free gas accumulations which when connected mimic the geometry of the seafloor. The most likely lithologic explanation for these high amplitude patches within weak BSRs, is the concept of segmented BSRs which is also seen in the Gulf of Mexico. The bright ―gas‖ anomalies are inferred to correlate with sand-rich high permeability layers while the weak BSR could be due to low saturations of gas in clay-rich low permeability layers. The weak BSR beneath the Puke Ridge is indicative of low and patchy gas saturations in low-permeability reservoir rocks while high amplitude patches found in this area may indicate high-permeability sands that may be attractive reservoir rocks for future gas hydrate production.</p>

Numerical Modeling of Sand Production Potential Estimation and Passive Control Optimization: A Case Study

2018 ◽  
Author(s):  
Eva Lopez-Puiggene ◽  
Nubia Aurora Gonzalez-Molano ◽  
Jose Alvarellos-Iglesias ◽  
Jose M. Segura ◽  
M. R. Lakshmikantha
Keyword(s):  
Stress State ◽  
High Resolution ◽  
Plastic Strain ◽  
Pore Pressure ◽  
In Situ Stress ◽  
Point Of View ◽  
Wellbore Stability ◽  
Sand Production ◽  
Production Stress

Solids/sand production is an unintended byproduct of the hydrocarbon production that, from an operational point of view, might potentially lead to undesirable consequences. This paper focuses on a study centered in the geomechanical perspective for solids production. An integrated workflow is presented to analyze the combined effect of reservoir pore-pressure, drawdown, in-situ stress, rock properties and well/perforations orientation on the onset of solid production. This workflow incorporates analyses at multiple scales: rock constitutive modeling at lab scale, 1D geomechanical models at wellbore scale along well trajectories, a 3D geomechanical model at the reservoir scale and 3D/4D high resolution reservoir - geomechanical coupled models at the well and perforation scale. 1D geomechanical models were built using log and field data, drilling experience and laboratory tests in order to characterize in situ stresses, pore pressure and rock mechanics properties (stiffness and strength) profiles for several wells. Rock shear failure mechanism was also analyzed in order to build a pre-drill model and evaluate the wellbore stability from a geomechanical point of view. Pre-production stress modeling was simulated to obtain a representative initial stress state integrating 1D geomechanics well results, 3D dynamic model and seismic interpretations. Mechanical properties were distributed considering properties calculated in the 1D geomechanical models as input. 3D stress field was validated with in-situ stress profiles from 1D modeling results. This simulated pre-production stress state was then used as an initial condition for the reservoir - geomechanical coupled simulations. Effective stress changes and deformations associated to pore pressure changes were calculated including the coupling between reservoir and geomechanical modeling. Finally, a 3D/4D high resolution well scale reservoir - geomechanical coupled numerical model was built in order to determine the threshold of sand production. A limit of plastic strain was obtained based on numerical simulations of available production data, DST and ATWC tests. This critical plastic strain limit was used as a criterion (strain-based) for rock failure to define the onset of sand production as a function of pore pressure, perforation orientation and rock strength. Conclusions regarding the perforation orientations related to the possibility of producing solids can support operational decisions in order to avoid undesirable solid production and therefore optimize the production facilities capacity and design to handle large amounts of solids and/or the clogging of the well.

The ability of rock physics models to infer marine in situ pore pressure

2014 ◽  
Vol 15 (12) ◽  
pp. 4769-4780 ◽  
Author(s):  
Matthew J. Hornbach ◽  
Michael Manga
Keyword(s):  
Pore Pressure ◽  
Rock Physics

Sensitivity study of rock-physics parameters for modeling time-lapse seismic response of Norne field

Geophysics ◽  
2013 ◽  
Vol 78 (6) ◽  
pp. D511-D523 ◽  
Author(s):  
Amit Suman ◽  
Tapan Mukerji
Keyword(s):  
Seismic Response ◽  
Pore Pressure ◽  
History Matching ◽  
Joint Inversion ◽  
Rock Physics ◽  
Clay Content ◽  
Time Lapse ◽  
Fluid Substitution ◽  
Seismic Modeling ◽  
Sensitive Parameters

Time-lapse seismic modeling is an important step in joint inversion of time-lapse seismic and production data of a field. Rock-physics analysis is the basis for modeling the time-lapse seismic data. However, joint inversion of both types of data for estimation of reservoir parameters is highly nonlinear and complex with uncertainties at each step of the process. So it is essential, before proceeding with large-scale history matching, to investigate sensitive rock-physics parameters in modeling the time-lapse seismic response of a field. We used the data set of the Norne field to investigate sensitive parameters in time-lapse seismic modeling. We first investigated sensitive parameters in the Gassmann’s equation. The investigated parameters include mineral properties, water salinity, pore pressure, and gas-oil ratio. Next, we investigated parameter sensitivity for time-lapse seismic modeling of the Norne field. The investigated rock-physics parameters are clay content, cement fraction, average number of contact grains per sand, pore pressure, and fluid mixing. We observed that the average number of contact grains per sand had the most impact on time-lapse seismic modeling of the Norne field. The clay content was the most sensitive parameter in fluid substitution for calculating seismic velocities of the Norne field. Salinity and pore pressure had minimal impact on fluid substitution for this case. This sensitivity analysis helps to select important parameters for time-lapse (4D) seismic history matching, which is an important aspect of joint inversion of production and time-lapse seismic modeling of a field.

Development of Time Lapse VSP Integration Workflow: A Case Study at Farnsworth CO2-EOR Project

2021 ◽  
Author(s):  
Marcia McMillan ◽  
Robert Will ◽  
Tom Bratton ◽  
William Ampomah ◽  
Hassan Khaniani
Keyword(s):  
Effective Stress ◽  
Penalty Function ◽  
Seismic Velocity ◽  
Rock Physics ◽  
Time Lapse ◽  
Fluid Substitution ◽  
3D Seismic ◽  
Site Specific ◽  
Seismic Velocity Changes ◽  
Velocity Changes

Abstract This study aims to develop a 4D Vertical Seismic Profile (VSP) integration workflow to improve the prediction of subsurface stress changes. The selected study site is a 5-spot pattern within the ongoing CO2-EOR operations at the Farnsworth Field Unit FWU in Ochiltree County, Texas. The specific pattern has undergone extensive geological and geomechanical characterization through the acquisition of 3D seismic data, geophysical well logs, and core. This workflow constrains a numerical hydromechanical model by applying a penalty function formed between "modeled" versus "observed" time-lapse compressional and shear seismic velocity changes. Analyses of geophysical logs and ultra-sonic measurements on core exhibit measurable sensitivities to changes in both fluid saturation and mean effective stress. These data are used to develop a site-specific rock physics model and stress-velocity relationship, which inform the numerical models used to generate the "modeled" portion of the penalty function. The "observed" portion of the penalty function is provided by a novel elastic full-waveform inversion of the available 3D baseline and three monitor surveys to produce high-quality estimates of time-lapse compressional and shear seismic velocity changes. The modeling workflow accounts sequentially for fluid substitution and stress impacts. Hydrodynamic and geomechanical properties of the 3D coupled numerical model are estimated through geostatistical integration of well log and core data with 3D seismic inversion products. Changes in seismic velocities due to fluid substitution are computed using the Biot-Gassmann workflow and site-specific rock physics. Stress impacts on time-lapse seismic velocity changes are modeled from the effective stress output of the hydromechanical model and are initially based on the velocity versus effective stress relationship extracted from core mechanical testing. Based on the principle of superposition of seismic wavefields, seismic velocity changes attributed to fluid substitution and that due to changes in mean effective stress are treated as linearly additive. The modeled results are upscaled using Backus averaging to reconcile scale discrepancies between the modeled and measured datasets to formulate the penalty function. This manuscript presents the forward modeling process and concludes that for the base case, the seismic velocity changes due to mean effective stress dominates over the seismic velocity changes attributed to fluid substitution because of the extensive range of the pressure perturbations. Successful minimization of this penalty function calibrates the coupled hydrodynamic geomechanical numerical model and affirms the suitability of acoustic time-lapse measurements such as 4D-VSP for geomechanical calibration.

Quantitative CO2 monitoring workflow

2020 ◽  
Author(s):  
Bastien Dupuy ◽  
Anouar Romdhane ◽  
Peder Eliasson
Keyword(s):  
Pore Pressure ◽  
Gravity Data ◽  
Rock Physics ◽  
P Wave ◽  
Added Value ◽  
Monitoring Data ◽  
Storage Site ◽  
High Porosity ◽  
Uncertainty Range ◽  
Fluid Saturation

&lt;p&gt;CO&lt;sub&gt;2&lt;/sub&gt; storage operators are required to monitor storage safety during injection with a long-term perspective (Ringrose and Meckel, 2019), implying that efficient measurement, monitoring and verification (MMV) plans are of critical importance for the viability of such projects. MMV plans usually include containment, conformance and contingency monitoring. Conformance monitoring is carried out to verify that observations from monitoring data are consistent with predictions from prior reservoir modelling within a given uncertainty range. Quantitative estimates of relevant reservoir parameters (e.g. pore pressure and fluid saturations) are usually derived from geophysical monitoring data (e.g. seismic, electromagnetic and/or gravity data) and potential prior knowledge of the storage reservoir.&lt;/p&gt;&lt;p&gt;In this work, we describe and apply a two-step strategy combining geophysical and rock physics inversions for quantitative CO&lt;sub&gt;2&lt;/sub&gt; monitoring. Bayesian formulations are used to propagate and account for uncertainties in both steps (Dupuy et al., 2017). We apply our workflow to data from the Sleipner CO&lt;sub&gt;2&lt;/sub&gt; storage project, located offshore Norway. At Sleipner, the CO&lt;sub&gt;2&lt;/sub&gt; has been injected at approx. 1000 m deep, in the high porosity, high permeability Utsira aquifer sandstone since 1996 with an approximate rate of 1 million tonnes per year. We combine seismic full waveform inversion and rock physics inversion to show that 2D spatial distribution of CO&lt;sub&gt;2&lt;/sub&gt; saturation can be obtained. Appropriate and calibrated rock physics models need to take into account the way fluid phases are mixed together (uniform to patchy mixing) and the trade-off effects between pore pressure and fluid saturation. For the Sleipner case, we show that the pore pressure build-up can be neglected and that the derived CO&lt;sub&gt;2&lt;/sub&gt; saturation distributions mainly depend on P-wave velocities and on the rock physics model. The CO&lt;sub&gt;2&lt;/sub&gt; saturation is larger at the top of the reservoir and the mixing tends to be more uniform. These mixing properties are, however, one of the main uncertainties in the inversion. We discuss the added value of a joint rock physics inversion approach, where multi-physics (electromagnetic, seismic, gravimetry), and multi-parameter inversion can be used to reduce the under-determination of the inverse problem and to better discriminate pressure, saturation, and fluid mixing effects.&lt;/p&gt;&lt;p&gt;Acknowledgements:&lt;/p&gt;&lt;p&gt;This publication has been produced with support from the NCCS Centre, performed under the Norwegian research program Centres for Environment-friendly Energy Research (FME). The authors acknowledge the following partners for their contributions: Aker Solutions, Ansaldo Energia, CoorsTek Membrane Sciences, Emgs, Equinor, Gassco, Krohne, Larvik Shipping, Lundin, Norcem, Norwegian Oil and Gas, Quad Geometrics, Total, V&amp;#229;r Energi, and the Research Council of Norway (257579/E20).&lt;/p&gt;&lt;p&gt;References:&lt;/p&gt;&lt;p&gt;Dupuy, B., Romdhane, A., Eliasson, P., Querendez, E., Yan, H., Torres, V.&amp;#160;A., and Ghaderi, A. (2017). Quantitative seismic characterization of CO&lt;sub&gt;2&lt;/sub&gt; at the Sleipner storage site, North Sea. Interpretation, 5(4):SS23&amp;#8211;SS42.&lt;/p&gt;&lt;p&gt;Ringrose, P.&amp;#160;S. and Meckel, T.&amp;#160;A. (2019). Maturing global CO&lt;sub&gt;2&lt;/sub&gt; storage resources on offshore continental margins to achieve 2DS emissions reductions. Scientific Reports, 9(1):1&amp;#8211;10.&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document