Full-field Model Research Articles

Full field modeling of dynamic recrystallization in a CPFEM context – Application to 304L steel

In this work the recently proposed full field approach to model dynamic recrystallization [1] is applied to model 304L steel. The framework couples a CPFEM (crystal plasticity finite element method) model with a LS-FE (level-set finite element method) for grain boundary migration and phenomenological laws. 304L steel samples are subjected to thermomechanical tests and their flow behaviour is characterized, additionally Electron Back Scattered Diffraction (EBSD) is used to study microstructure evolutions. Part of the experimental data is used to calibrate the model parameters and describe their evolution as a function of the thermomechanical conditions. The calibrated model is used to predict the microstructural evolution of 304L steel, the results are compared with the remaining experimental measurements. The comparison shows that the model correctly predicts the flow behaviour and recrystallization fraction evolution. However the results also show that the use of classical phenomenological models limit the model capability to predict grain size evolution. Different approaches to improve the model grain size prediction are presented and compared, the results show significant improvements when compared with experimental data.

Learnings Applied to Reservoir Simulation of Unconventional Plays

This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 199164, “Applied Learnings in Reservoir Simulation of Unconventional Plays,” by Raphael Altman, SPE, Roberto Tineo, SPE, and Anup Viswanathan, SPE, Schlumberger, et al., prepared for the 2020 SPE Latin American and Caribbean Petroleum Engineering Conference, Bogota, Colombia, 17-19 March. The paper has not been peer reviewed. Reservoir simulation is valuable in understanding dynamics of unconventional reservoirs. Applications include estimating long-term production behavior, enhancing well-spacing and pad-modeling efficiency, optimizing completion and stimulation of horizontal wells, and understanding production drivers that cause differences in productivity between wells. In the complete paper, the authors revisit fundamental concepts of reservoir simulation in unconventional reservoirs and summarize several examples that form part of an archive of lessons learned. Reservoir Simulation Applications in Unconventionals Reservoir simulation plays an important role in many stages of unconventional reservoir field development. In the initial pilot phase, a calibrated reservoir simulation model can provide an indication of estimated ultimate recovery (EUR), which is advantageous given few wells with short production time. EUR evaluation with incorporated uncertainties is a key variable in asset evaluation and investment decisions. During the ramp and development phases, reservoir simulation aids completion optimization by providing a link between completion parameters, such as cluster spacing and stimulation pumping parameters, and a well’s production. Extending this idea further, the integrated nature of reservoir simulation enables identification of production drivers and understanding of why wells are producing differently. During the mature stages of unconventional reservoir development, well spacing and hydraulic fracture and pressure interference, together with refracturing, require advanced modeling techniques that can include a combination of hydraulic fracture simulation, 3D stress simulations, and advanced reservoir simulation. Reservoir Simulation Modeling in Unconventionals Unconventional reservoirs are heterogeneous across multiple scales and exhibit variations in production performance across wells. The production variation is influenced by a large variation in production drivers that simultaneously affect the production. Examples of these drivers include reservoir properties such as hydrocarbon-filled porosity, moveable hydrocarbons, matrix permeability, relative permeability and pressure/volume/temperature, completion properties such as stress-state and natural fractures, and stimulation (pumping) parameters. Reservoir simulation constitutes one of the best tools to understand the dominant production drivers because of the multidisciplinary data required to build simulation models for unconventional reservoirs. Because of the orders of magnitude of difference in matrix permeability between conventional and unconventional reservoirs, pressure gradients from the sandface to the formation (pressure drawdowns) are larger in unconventional reservoirs and drainage radii are more likely to be smaller. Therefore, in the case of shale reservoirs, single-well models usually suffice except for the case of multiwell pads. Very fine grid cells (on the order of inches to a few feet) are used close to, and immediately surrounding, the perforation clusters, whereas in conventional reservoirs, coarser grid cells are used, especially in full-field models, even with local grid refinements.

Simulation of Immiscible Water-Alternating-CO2 Flooding in the Liuhua Oilfield Offshore Guangdong, China

In this paper, the immiscible water-alternating-CO2 flooding process at the LH11-1 oilfield, offshore Guangdong Province, was firstly evaluated using full-field reservoir simulation models. Based on a 3D geological model and oil production history, 16 scenarios of water-alternating-CO2 injection operations with different water alternating gas (WAG) ratios and slug sizes, as well as continuous CO2 injection (Con-CO2) and primary depletion production (No-CO2) scenarios, have been simulated spanning 20 years. The results represent a significant improvement in oil recovery by CO2 WAG over both Con-CO2 and No-CO2 scenarios. The WAG ratio and slug size of water affect the efficiency of oil recovery and CO2 injection. The optimum operations are those with WAG ratios lower than 1:2, which have the higher ultimate oil recovery factor of 24%. Although WAG reduced the CO2 injection volume, the CO2 storage efficiency is still high, more than 84% of the injected CO2 was sequestered in the reservoir. Results indicate that the immiscible water-alternating-CO2 processes can be optimized to improve significantly the performance of pressure maintenance and oil recovery in offshore reef heavy-oil reservoirs significantly. The simulation results suggest that the LH11-1 field is a good candidate site for immiscible CO2 enhanced oil recovery and storage for the Guangdong carbon capture, utilization and storage (GDCCUS) project.

Crystallographic orientation and spatially resolved damage in a dispersion-hardened Al alloy

The in-situ neutron diffraction technique, in combination with both the full-field crystal elasto-viscoplastic finite element model and microstructural characterization, was used to study the deformation-induced damage anisotropy in a commercial Al alloy, subjected to uniaxial tensile and cyclic loading. The simulations capture well the crystallographic-orientation-dependent lattice strain behavior. The hard grains, e.g. those orientated with the <111> and <422> orientations parallel with the uniaxial loading direction (LD), feature large Taylor factors and seem more prone to form damage-related band structures. Their effective elastic moduli decrease with the accumulation of damage, which are different from the soft grains orientated with the <200> orientation along the LD. Correlation between the distribution of voids and that of the residual lattice strain developed after failure may exist. The maximum tensile type residual lattice strain observed after failure may be resulted from the band structure formed in the hardest <111> grains. It was revealed that the band structure triggered by the hard particles could be one of sources of damage. In addition, while the specimen was obviously damaged, a fast stress relief was evidenced after unloading from the tension, especially at the beginning of unloading. Our present investigations provide a novel method for exploring the damage mechanisms of polycrystalline materials during plastic deformation.

New Modeling and Simulation Techniques Optimize Completion Design and Well Spacing

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 194367, “Optimize Completion Design and Well Spacing With the Latest Complex Fracture Modeling and Reservoir-Simulation Technologies—A Permian Basin Case Study With Seven Wells,” by Hongjie Xiong, SPE, and Songxia Liu, University Lands, and Feng Feng, SPE, Texas A&amp;M University, et al., prepared for the 2019 SPE Hydraulic Fracturing Technology Conference, The Woodlands, Texas, 5–7 February. The paper has not been peer reviewed. Proper lateral and vertical well spacing is critical for efficient development of unconventional reservoirs. Much research has focused on lateral well spacing but little on vertical spacing, which is challenging for stacked-bench plays such as the Permian Basin. Following a previous, successful single-well study in paper SPE 189855, the authors have performed a seven-well case study in which the latest complex fracture modeling and reservoir-simulation technologies have been applied. This synopsis will concentrate on the methodology behind the study; the reader is encouraged to view the complete paper for specific comparisons of completion designs. Introduction Complex-fracture-modeling tools are used frequently to study well spacing. Most research has focused on lateral well spacing rather than on vertical spacing, though the industry has seen many fracturing hits and hydraulic communications between wellbores placed vertically in stacked plays. Field pilot tests have been used extensively to test and optimize lateral and vertical well spacings and to optimize well-completion designs. These pilot tests, however, take considerable time to implement and are very expensive. In this multiple-well study, the authors used an established work flow to study the fracture interaction between wellbores and lateral and vertical well spacings. A calibrated model was then used to optimize well-completion designs for the Wolfcamp formation. Work Flow The work flow to build and calibrate the complex-fracture-network and reservoir-performance-simulation models, and then use the models to conduct sensitivity analysis on the fracture networks, resulted from different completion designs and corresponding well performance. Because some critical data sets are spread throughout a wide areA&amp;Mdash;including core data, comprehensive well-logging data, and geomechanical properties—the authors first built a regional geological model, then sliced the sector models from the regional model. This enabled use of available data that were spread sparsely across the area. On the basis of the well locations, a sector model was built by cutting a section from the regional geological model. In the process, the properties were repopulated with a finer grid size. Previous studies discussed using the seismic data to build a discrete fracture network (DFN). For the authors of this paper, however, the DFN represents not only the natural fracture networks but also includes geological bedding or layering information. Those beddings or layerings may be mechanical-weakness connections, which influence hydraulic-fracturing propagations. The detailed well-completion information was then plugged in. Seven-Well Case-History-Modeling Setup Seven wells drilled and completed in four different zones within the Wolfcamp formation were studied. A sector model was cut from the full-field (regional) model on the basis of the well locations, considering the possible fracture-propagation-modeling needs. The sector model covers a length of 12,600 ft, a width of 4,200 ft, and a thickness of 3,000 ft. In the process, a much finer grid size was used (refined from 300×300 ft in the regional model to 33×33 ft in the sector model) with consideration of perforation cluster spacings. Then, all formation properties were repopulated to the smaller grid cells with the same property models used in the regional model. The wellbores and perforations then were input into the sector model.

A new numerical framework for the full field modeling of dynamic recrystallization in a CPFEM context

This work describes the coupling of a level-set (LS) based numerical framework for microstructural evolutions modeling with a crystal plasticity finite element method (CPFEM), in order to propose a new full field approach dedicated to dynamic recrystallization (DRX) modeling. These developments are proposed for 3D polycrystalline metals subjected to large deformations at high temperatures.CPFEM is one of the best available alternatives to model the evolution of dislocation densities and misorientation during plastic deformation. The dislocation density and misorientation is then used as input data for the recrystallization model. Grain boundary migration (GBM) is modeled by using a kinetic law which links the velocity of the grain boundaries, described by LS functions, with the thermodynamic driving pressures. The nucleation of new grains is modeled by using phenomenological laws, which define the number of nucleation sites as a function of the dislocation density and the misorientation. The link between the CPFEM and the GBM model gives an accurate description of the DRX phenomenon, which is intended to model industrial processes.In this work the methods and the coupling algorithm are presented, along with an analysis of the different numerical parameters and strategies to define nucleation. The calibration and validation of the model against experimental data for 304L steel will be presented in a future work.

Evaluation of Polymer Flooding in a Highly Stratified Heterogeneous Reservoir. A Field Case Study

Oil and gas companies are looking for proven hydrocarbon reserves from their mature drained reservoirs to extend the production and economic life of these fields. The chemical enhanced oil recovery (CEOR) is an attractive water-based EOR method for these mature fields. The polymer flooding (PF) is a widely applied process in reservoirs with low sweep efficiency after the water flooding (WF). The target Colombian field has one of the first polymer pilots in the region with positive results of oil recovery in “A” sands. Thus, the operator is interested in the expansion of PF for the same reservoir and even in deeper reservoir sands. This paper focuses in the evaluation of different scenarios of PF for the producer in layers A and B with a mechanistic simulation model, thus obtaining new recommendations for the recovery strategy in the field. A sector model was constructed from a full field model using a commercial reservoir simulator to the in-house chemical flooding reservoir simulator: UTCHEMRS. This sector model was also migrated to a second commercial simulator allowing a performance comparison for these three simulators. UTCHEMRS model results were compared with the commercial simulators through the history matching (HM) phase. The primary and waterflood history match was in agreement with the field data. Simulation results suggested that PF for the base case in “A” sands presented an incremental oil recovery of up to 12% additional to water flooding. Additionally, PF was extended to the lower layer “B” sand to investigate the potential of polymer injection. The PF injection in both reservoirs simultaneously loses sweep efficiency and decreases the oil recovery to about 3%. However, a hypothetical case of new infill producer wells with the objective of testing the individual reservoir performance has revealed that PF is having significant upside from B sands as well.

Adjoint method acceleration protocols for model maturation to update static models with time-lapse reservoir surveillance data

We develop an ensemble model-maturation method that is based on the Randomized Maximum Likelihood (RML) technique and adjoint-based computation of objective function gradients. The new approach is especially relevant for rich data sets with time-lapse information content. The inversion method that solves the model-maturation problem takes advantage of the adjoint-based computation of objective function gradients for a very large number of model parameters at the cost of a forward and a backward (adjoint) simulation. The inversion algorithm calibrates model parameters to arbitrary types of production data including time-lapse reservoir-pressure traces by use of a weighted and regularized objective function. We have also developed a new and effective multigrid preconditioning protocol for accelerated iterative linear solutions of the adjoint-simulation step for models with multiple levels of local grid refinement. The protocol is based on a geometric multigrid (GMG) preconditioning technique. Within the model-maturation workflow, a deep-learning technique is applied to establish links between the mesh-based inversion results (e.g., permeability-multiplier fields) and geologic modeling parameters inside a static model (e.g., object dimensions, etc.). Our workflow integrates the learnings from inversion back into the static model, and thereby, ensures the geologic consistency of the static model while improving the quality of the ensuing dynamic model in terms of honoring production and time-lapse data, and reducing forecast uncertainty. This use of deep learning (DL) to post-process the model-maturation outcome effectively converts the conventional continuous-parameter history-matching result into a discrete tomographic inversion result constrained to geological rules encoded in training images.We demonstrate the practical utilization of the adjoint-based model-maturation method on a large time-lapse reservoir-pressure data set using an ensemble of full-field models from a reservoir case study. The model-maturation technique effectively identifies the permeability modification zones that are consistent with alternative geological interpretations and proposes updates to the static model. Upon these updates, the model not only agrees better with the time-lapse reservoir-pressure data but also better honors the tubing-head pressure as well as production logging data. We also provide computational performance indicators that demonstrate the accelerated convergence characteristics of the new iterative linear solver for adjoint equations.

Interdependencies between physical, design and operational parameters for direct use geothermal heat in faulted hydrothermal reservoirs

Interest in direct use geothermal systems is increasing due to their ability to supply renewable, environmentally friendly heat. Such systems are mostly developed in conduction dominated geological settings where faults are often encountered. Interdependencies between physical, design and operational parameters make it difficult to assess the performance of such systems. Interaction with faults could potentially have adverse effects on system lifetime, generated Net Present Value (NPV) and produced energy. In this work a single doublet system in the enthalpy range of 140 kJ/kg to 350 kJ/kg is analysed using COMSOL Multiphysics. A choice of design (well spacing and placement), physical (layered reservoir, fault flow properties, fault throw) and operational (injection and production flow rates) parameters are considered in a full factorial design that includes 2430 3D reservoir simulations. Results show that fault flow properties characterization is more significant than fault throw structural characterization. For the considered reservoir properties, increasing the flow rate four times results in an NPV increase of a factor seven, despite the shorter system lifetime. A sealing fault renders the system lifetime less sensitive to the doublet positioning. Synthetic model results shown can serve as guidelines to reducing full scale field models. Importance and relevance of these results remains very high for horizontally homogeneous, layered reservoirs. The analysis expands the understanding of interdependencies for direct use geothermal systems and informs on their further development.

Hierarchical parameterization and compression-based object modelling of high net:gross but poorly amalgamated deep-water lobe deposits

Deep-water lobe deposits are arranged hierarchically and can be characterized by high net:gross ratios but poor sand connectivity due to thin, but laterally extensive, shale layers. This heterogeneity makes them difficult to represent in standard full-field object-based models, since the sands in an object-based model are not stacked compensationally and become connected at a low net:gross ratio. The compression algorithm allows the generation of low-connectivity object-based models at high net:gross ratios, by including the net:gross and amalgamation ratios as independent input parameters. Object-based modelling constrained by the compression algorithm has been included in a recursive workflow, permitting the generation of realistic models of hierarchical lobe deposits. Representative dimensional and stacking parameters collected at four different hierarchical levels have been used to constrain a 250 m-thick, 14 km 2 model that includes hierarchical elements ranging from 20 cm-thick sand beds to more than 30 m-thick lobe complexes. Sand beds and the fine-grained units are represented explicitly in the model, and the characteristic facies associations often used to parameterize lobe deposits are emergent from the modelling process. The model is subsequently resampled without loss of accuracy for flow simulation, and results show clearly the influence of the hierarchical heterogeneity on drainage and sweep efficiency during a water-flood simulation.

Unique Infill Configuration To Unlock Additional Barrels in the Boscán Heavy-Oil Water-Injection Project

Summary Boscán is a giant multibillion-barrel heavy-oil (10.5 °API and asphaltic) field in Venezuela. Although a large part of the field is on primary production with a low recovery factor (&amp;lt;6%), water injection has been successfully implemented in portions of the field for more than 15 years, with improved recovery. High-mobility-ratio-waterflood (HMRWF) behavior and associated key production mechanisms obtained from detailed field-data analysis and dynamic modeling are presented. A novel and unique infill configuration is also proposed to further improve recovery in this environment with a high (or adverse) mobility ratio. Water injection in such heavy oil was previously considered not effective by the industry because of adverse mobility ratio. However, water injection for pressure maintenance (WIPM) was successfully implemented using a new pattern configuration, a pseudo-1-3-1 inverted- spot pattern (an additional row of producers between conventional-pattern rows). Field-data and reservoir-simulation models show increased reservoir pressure up to the second row of producers from the injector. The pressure support is used to significantly improve recovery using the unique configuration at low water cut. WIPM has already resulted in significant reserves addition. Current production from water-injection areas is approximately 40,000 MBOPD (or approximately 47% of field production). However, it is estimated that because of high oil viscosity, a significant amount of oil remains bypassed in the WIPM area. An infill opportunity was identified from an integrated reservoir-management study that included detailed WIPM data analysis and dynamic (mechanistic and full-field) modeling. A unique infill configuration is proposed that conceptually uses the current injectors with an additional row of producers between the existing first and second row of the producers. This configuration has the potential to economically unlock millions of barrels of bypassed oil and significantly increase recovery in this prolific heavy-oil field. This study provides insights into HMRWF behavior, evaluating the relative effect of displacement vs. pressure. The unique and novel infill configuration can be used to improve recovery, a step vital to monetize this large resource in the low-price environment.

Comparison of simplified techniques for solving selected coupled electroheat problems

Purpose The purpose of this paper is to compare different reduced-order models for models of control of induction brazing process. In the presented application, the problem is to reconstruct temperature at the points of interests (hot spots) from information measured at accessible places. Design/methodology/approach The paper describes the process of induction brazing. It presents the full field model and evaluates the possibilities for obtaining reduced models for temperature estimation. The primary attention is paid to the model based on proper orthogonal decomposition (POD). Findings The paper shows that for the given application, it is possible to find low-order estimator. In the examined linear case, the best estimator was created using POD reduced model together with the linear Kalman filter. Research limitations/implications The authors are aware of two main limitations of the presented study: material properties are considered linear, which is not a completely realistic assumption. However, if strong coupling and nonlinear material parameters are considered, the model becomes unsolvable. The process and measurement uncertainties are not considered. Originality/value The paper deals with POD of multi-physics 3 D application of induction brazing. The paper compares 11 different methods for temperature estimator design.

Spectral methods for full-field micromechanical modelling of polycrystalline materials

Abstract Modelling the mechanical behavior of polycrystalline materials based on their evolving microstructure and the anisotropic properties of their constituent single crystal grains is nowadays an indispensable tool to establish physically-based relationships between processing, structure and properties of this ubiquitous type of materials. These models have found multiple applications in Material Science, Mechanics of Materials, and Earth Sciences. This article reviews the specialization to polycrystalline materials of a spectral formulation developed in the last two decades to efficiently solve the micromechanical behavior of heterogeneous materials. This review provides a consolidated account, using a unified notation, of the various numerical implementations of the spectral formulation for polycrystalline materials deforming in different constitutive regimes, each of which requires specific numerical strategies. Examples are given that illustrate these implementations for each constitutive behavior, as well as comparisons with other models, and applications to different materials, including the use of experimental data for input of the calculations and validation of the model predictions.

Full Field and Mean Field Modeling of Grain Growth in a Multiphase Material Under Dry Conditions: Application to Peridotites

AbstractWe present a full field framework based on the level‐set approach, which enables to simulate grain growth in a multiphase material. Our formalism permits to take into account different types of second phases, which can be static or dynamic (i.e., evolving also by grain growth) and reproduce both transient (evolving relative grain sizes) and steady‐state structures. We use previously published annealing experiments of porous olivine or olivine and enstatite mixtures to constrain the parameters of the full field model, and then analyze the results of a peridotite‐like annealing simulation. The experimental grain growth kinetics is very well reproduced while the simulated microstructure morphologies show some differences with experimental ones. We then propose a mean field model calibrated thanks to the full field simulations, which allow us to predict the mean grain size evolution depending on the simplified peridotite composition (e.g., second phase mean grain sizes, fractions).

Mean field and full field modelling of microstructure evolution and phase transformations during hot forming and cooling of low carbon steels

Mean field and full field modelling of microstructure evolution and phase transformations during hot forming and cooling of low carbon steels

Quantifying the Contribution of Crystallographic Texture and Grain Morphology on the Elastic and Plastic Anisotropy of bcc Steel

The influence of grain shape and crystallographic orientation on the global and local elastic and plastic behaviour of strongly textured materials is investigated with the help of full-field simulations based on texture data from electron backscatter diffraction (EBSD) measurements. To this end, eight different microstructures are generated from experimental data of a high-strength low-alloy (HSLA) steel processed by linear flow splitting. It is shown that the most significant factor on the global elastic stress–strain response (i.e., Young’s modulus) is the crystallographic texture. Therefore, simple texture-based models and an analytic expression based on the geometric mean to determine the orientation dependent Young’s modulus are able to give accurate predictions. In contrast, with regards to the plastic anisotropy (i.e., yield stress), simple analytic approaches based on the calculation of the Taylor factor, yield different results than full-field microstructure simulations. Moreover, in the case of full-field models, the selected microstructure representation influences the outcome of the simulations. In addition, the full-field simulations, allow to investigate the micro-mechanical fields, which are not readily available from the analytic expressions. As the stress–strain partitioning visible from these fields is the underlying reason for the observed macroscopic behaviour, studying them makes it possible to evaluate the microstructure representations with respect to their capabilities of reproducing experimental results.

Characterization and modeling of [formula omitted] twin banding in magnesium

We experimentally and numerically examined the localization behavior of {101¯2} extension twins in strongly and weakly textured AZ31 and ZEK100 magnesium alloys as they depart from the surface toward the center of the sheet under the mechanical action of three-point bending. Strain measurement analysis using digital image correlation revealed that twin banding occurs only in the sharply textured AZ31, but with a characteristic spacing between the bands which decreases with the twin height and applied strain. ZEK100 did not exhibit any ordered localization of bands and behaved as a “true” polycrystal. This finding is in agreement with micromechanical calculations by the present authors . We show that full-field plasticity finite element crystal plasticity model was unable to capture many important 2D features of the twin banding. This suggest that twin shear transfer, non-local effects, and the third dimension effects should be included into this model.

Study of the influence of δ-ferrite on the TRIP effect of a low-density high aluminum steel by using full-field crystal plasticity modeling

Low-density high aluminum transformation induced plasticity (TRIP) steel is a new developed light-weight structural material. In the conventional casting (CC) TRIP steel, however, the presence of high Al content results in the formation of coarse dendritic δ-ferrite, which seriously deteriorates the performance of the material. The spray forming process show good potential to refine and homogenize the microstructure. It was found that the δ-ferrite in the spray formed (SF) TRIP steel is refined remarkably and its distribution is more homogeneous. Uniaxial tension tests demonstrate that the ductility of the SF TRIP steel is increased by 5% compared with the CC TRIP steel. The difference of their properties is mainly due to the different morphologies of the δ-ferrite. We further employed a full-field crystal plasticity (CP) modeling to probe the micromechanical mechanisms in details, and a new simplified model was proposed to describe the TRIP effect and phase transformation. The material parameters of three individual phases δ-ferrite (δ), austenite (γ), and martensite (α′) for the CP model were identified from the loading curves of nanoindentation tests. Through the simulation, it was found that compared with SF TRIP steel, there are large deformation bands formed in the CC TRIP steel during the deformation. These areas are the regions in which austenite has the priority to transform into martensite. It is the initial heterogeneity of deformation in the CC TRIP steel that results in the heterogeneous phase transformation, and thus intensifies the heterogeneous deformation at the phase boundaries, which ultimately accelerates the generation of cracks.

Analysis of Remote Displacement Patterns Monitored by Tiltmeters During Fluid Injection Into Reservoirs

In order to take far-field translational tilts into account during studying reservoir flow process of CO2 injection, a group of tiltmeters were installed as array covering estimate range of ground spreading from the injection well. The measurements were applicable to ground deformations during a fracturing stimulation treatment, a short-term test of CO2 injection into relatively shallow coal seams and a CO2 injection into deep saline aquifer. An attempt to quantitatively model the rational association between reservoir volumetric disturbance underground and its induced corresponding rather slight distortion on surface was presented. It is as well demonstrated how to sufficiently manipulate vertical unstructured and horizontal divergent model numerical discretization, which eventually makes it feasible to study mechanism between reservoir flow and reservoir Geomechanics by full-field reservoir model. The potential algorithms to improve the computational efficiency and an actual demand for an ambitious solver to inverse coupling problem are finally discussed. The study proposed the development of high-efficiency software package fully capable of dealing with reservoir flow and reservoir Geomechanics so as to implement the history match study not only on a reservoir itself being injected but also including the full field deformation performance up to the costly ground displacement monitoring data.

Quantitative seismic reservoir modeling — Model-based probabilistic inversion for optimal field development

Full-field reservoir models provide key input to annual business plans and reserve booking. They support the long-term field development plan by enabling well target optimization, identification of infill opportunities, water-flood management, and well-surveillance and intervention strategies. It is crucial to constrain the model with all available static and dynamic data to improve its predictive power for confident decision making. Across Shell's global deepwater portfolio, a model-based probabilistic seismic amplitude-variation-with-offset (AVO) inversion methodology is used to constrain reservoir properties as part of a comprehensive quantitative seismic reservoir modeling workflow. Promise, a proprietary probabilistic inversion tool, estimates values of reservoir properties and quantifies their uncertainties through repeated forward modeling and automated quality checking of synthetic against recorded seismic data. During workflow execution, available geologic, petrophysical, and geophysical data are incorporated. As a consequence, the reservoir models are consistent with all relevant subsurface data following their update through inversion. Model-based inversion establishes a direct link between static model properties and elastic impedances. Probabilistic inversion output is an ensemble of posterior static models. The inversion process automatically sorts through the ensemble. It can directly provide low, mid, and high cases of the inverted models that are ready to be used in hydrocarbon volume estimation and multiscenario dynamic modeling for history matching and production forecasting. For successful and efficient delivery of full-field reservoir models with uncertainty assessment using model-based probabilistic AVO inversion, early integration of interdisciplinary subsurface data and cross-business collaboration are key.