bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Improved Inversion Workflow Jointly Assimilating 4D Seismic and Production Data
Authors: Jin Long , Gao Guohua , Vink Jeroen C. , Chen Chaohui , Weber Daniel , Alpak Faruk O. , Hoek Paul van , Pirmez Carlos 
Published: June 2012

Abstract
Quantitative integration of 4D seismic data with production data into reservoir models is a challenging task. One important issue is how to properly quantify the uncertainty, or the posterior probability distribution (PPD). The Very Fast Simulated Annealing (VFSA) is a stochastic searching method, whereas the Simultaneous Perturbation and Multivariate Interpolation (SPMI) is a model-based local searching method. The stochastic features of the VFSA provide the feasibility of identifying possible multiple peaks of a PPD, but it converges very slowly. On the other hand, the model-based SPMI method has the advantages of effectively utilizing the smooth features of an objective function, and thus can converge to local optimum very quickly. More importantly, the Hessian of the objective function, or the covariance matrix of the PPD, can be estimated by the SPMI method with satisfactory accuracy. However, it is very difficult to identify multiple optima by applying the SPMI method alone. In this paper, we propose an efficient joint inversion workflow by appropriately integrating the two derivative free optimization (DFO) methods. The complementary features of the two methods can further improve both applicability and efficiency of this joint inversion workflow. We tested the workflow with a 3D synthetic model and a real field case. Our results show that the integrated method is efficient and can deliver good results for jointly assimilating 4D seismic and production data.
Ekofisk 4D Seismic - Seismic History Matching Workflow
Authors: Tolstukhin Evgeny , Lyngnes Bjarne , Sudan Hari H. 
Published: June 2012

Abstract
This presentation outlines an integrated workflow that incorporates 4D seismic data into the Ekofisk field reservoir model history matching process. Successful application and associated benefits of the workflow benefits are also presented.
A seismic monitoring programme has been established at Ekofisk with 4D seismic surveys that were acquired over the field in 1989, 1999, 2003, 2006 and 2008. Ekofisk 4D seismic data is becoming a quantitative tool for describing the spatial distribution of reservoir properties and compaction. The seismic monitoring data is used to optimize the Ekofisk waterflood by providing water movement insights and subsequently improving infill well placement.
Reservoir depletion and water injection in Ekofisk lead to reservoir rock compaction and fluid substitution. These changes are revealed in space and time through 4D seismic differences. Inconsistencies between predicted 4D differences (calculated from reservoir model output) and actual 4D differences are therefore used to identify reservoir model shortcomings. This process is captured using the following workflow: (1) prepare and upscale a geologic model, (2) simulate fluid flow and associated rockphysics using a reservoir model, (3) generate a synthetic 4D seismic response from fluid and rock physics forecasts, and (4) update the reservoir model to better match actual production/injection data and/or the 4D seismic response.
The above-mentioned Seismic History Matching (SHM) workflow employs rock-physics modeling to quantitatively constrain the reservoir model and develop a simulated 4D seismic response. Parameterization techniques are then used to constrain and update the reservoir model. This workflow updates geological parameters in an optimization loop through minimization of a misfit function. It is an automated closed loop system, and optimization is performed using an in-house computer-assisted history matching tool using evolutionary algorithm.
In summary, the Ekofisk 4D SHM workflow is a multi-disciplinary process that requires collaboration between geological, geomechanical, geophysical and reservoir engineering disciplines to optimize well placement and reservoir management.
Adjoint-based History-Matching of Production and Time-lapse Seismic Data
Authors: Van Essen G. M. , Jimenez E. A. , Przybysz-jarnut J. P. , Horesh L. , Douma S. G. , van den Hoek P. J. , Conn A. , Mello U. T. 
Published: June 2012

Abstract
Time-lapse (4D) seismic attributes can provide valuable information on the fluid flow within subsurface reservoirs. This spatially-rich source of information complements the poor areal information obtainable from production well data. While fusion of information from the two sources holds great promise, in practice, this task is far from trivial. Joint Inversion is complex for many reasons, including different time and spatial scales, the fact that the coupling mechanisms between the various parameters are often not well established, the localized nature of the required model updates, and the necessity to integrate multiple data. These concerns limit the applicability of many data-assimilation techniques. Adjoint-based methods are free of these drawbacks but their implementation generally requires extensive programming effort. In this study we present a workflow that exploits the adjoint functionality that modern simulators offer for production data to consistently assimilate inverted 4D seismic attributes without the need for re-programming of the adjoint code. Here we discuss a novel workflow which we applied to assimilate production data and 4D seismic data from a synthetic reservoir model, which acts as the real - yet unknown - reservoir. Synthetic production data and 4D seismic data were created from this model to study the performance of the adjoint-based method. The seamless structure of the workflow allowed rapid setup of the data assimilation process, while execution of the process was reduced significantly. The resulting reservoir model updates displayed a considerable improvement in matching the saturation distribution in the field. This work was carried out as part of a joint Shell-IBM research project.
Wettability Determination by Equilibrium Contact Angle Measurements: Reservoir Rock- Connate Water System With Injection of CO2
Authors: Shojai kaveh N. , Berentsen C. W. , Rudolph E. S. , Wolf K-H. A. , Rossen W. R. 
Published: June 2012

Abstract
The injection of carbon dioxide (CO2) into depleted gas reservoirs and aquifers offer options for CO2-storage. CO2 sequestration is largely controlled by the interactions between CO2, reservoir fluid(s) in place and rock. In particular, the wettability of the rock matrix is a key factor for the fluid distribution and fluid displacement.
In this study, the wetting behavior of CO2-Bentheimer sandstone-water systems was investigated by means of visual contact-angle measurements. The experiments were conducted in a modified pendant drop cell (PDC) that allows captive-bubble contact-angle measurements at elevated temperatures and pressures. Contact angle measures were peformed with water that was fully (pre)-saturated with CO2. Multiple experiments were performed at constant temperature of 318K and pressures varying between 0.1-12 MPA which represent typical in-situ reservoir conditions. The experimental data shows that the contact angle and the size of the bubble converge to equilibrium in time. During this convergence period, the contact angle and the bubble size generally show a slight change as function of time. This can be contributed to the mass transfer and reduction in density of the CO2 during re-equilibration of the system. The experimental data shows a larger dependency of the contact angle on bubble size than on pressure. However, for bubbles with similar size, contact angle shows a slight increase as a function of pressure. However, for bubbles with similar size, contact angle shows a slight increase as function of pressure. All data shows that Bentheimer-water-CO2 systems remain water-wet even at high pressure.
A Comprehensive Workflow for Assisted History Matching Applied to a Complex Mature Reservoir
Authors: Van Doren Jorn , Van Essen Gijs , Wilson Ove , Zijlstra Ellen 
Published: June 2012

Abstract
Currently a multitude of techniques exist for (computer-)assisted history matching (AHM) of simulation models, each with their merits and limitations. In this paper, it is demonstrated how different AHM techniques can be combined to quickly reveal diagnostics of a subsurface model and to obtain a better model in less time, optimally using the strengths of each method. A completed field application of AHM will be presented, in which several AHM techniques are sequentially used to arrive at a history match on pressures and fluid rates and, equally important, an improved understanding of both the static and dynamic model.
The water flooded field, located in the Middle East, has decades of historical production data from twenty wells and is notoriously difficult to match. The first technique that has been applied involves Design of Experiments to generate proxies followed by Monte Carlo Markov Chain to find the ensemble of scalar parameters that give an improved match. Subsequently, adjoint-based history matching has been used to find the areas in the model that were under-modeled and needed additional attention of the subsurface team members.
Based on the results in this step of the workflow the static model has been improved such that it is consistent with the information in the production measurements. For this field, the AHM workflow has achieved a considerable reduction of history matching time. For general simulation studies this workflow is estimated to result in a time saving of 40% with respect to manual history matching. In addition, it results in an improved match and a better understanding of the static and dynamic subsurface uncertainties.
Integrated Reservoir Studies, Karachaganak Field, Republic of Kazakhstan
Authors: Francesconi A. , Bigoni F. , Albertini C. , Cominelli A. , Catalani C. , Tarantini V. , Imagambetov K. 
Published: June 2012

Abstract
Karachaganak field is one of the largest accumulations of gas-condensate in the world in production since 1985. Located in the northern Pricaspian Basin (Kazakhstan) the field is a Permo-Carboniferous isolated carbonate platform with a hydrocarbon column that resides within different environments of deposition. The distribution of reservoir properties has been largely debated because of both the depositional heterogeneity and the diagenetic overprint.
These uncertainties were assessed by analyzing and integrating the vast amount of geological and production data to build a predictive history matched reservoir model.
Seismic facies analysis, with support from outcrop analogues and integrated with field core and log data, reveals, within stratigraphic intervals, "Depositional Regions" (DRs) that ranges from platform interior bedded deposits to aggrading/prograding mounds, clinoforms, slopes and basin sediments. These DRs were first seismically mapped, identifying field scale heterogeneity, and then petrophysically characterized using geologic and dynamic data.
A sequence of progressively optimized models was built according to geologically meaningful concepts that make use of DRs and critical petrophysical issues (such as enhanced/matrix permeability, sealing barriers and dolomitization) were in parallel addressed. A reference model has been so defined and a history match of remarkable quality has been achieved for this complex heterogeneous reservoir.
The uncertainty was investigated in a pragmatic manner using HM as benchmark. The reservoir uncertainty decreases closer and closer to the wells, hence alternative models scenarios were built by gradually changing DRs petrophysical properties going away from the production wells. Using the distance and the magnitude of the perturbations as control parameters and the quality of history match as selection criterion, we could identify two &quot;end members??. These cases represent possible alternative scenarios both consistent with the geological data and still endorsed by a high quality history match, two reservoir models capable to give a significant spread in the production forecast.
Assisted History-Matching for the Characterization and Recovery Optimization of Fractured Reservoirs Using Connectivity Analysis
Authors: Lima A. De , Lange A. , Schiozer D. 
Published: June 2012

Abstract
An integrated optimization workflow was developed to characterize seismic and sub-seismic fault networks from history-matching. A fractal model of fault networks is optimized via the gradual deformation of stochastic realizations of fault density maps, fault spatial and length distributions. In order to facilitate the history-matching, connectivity analysis tools were developed for characterizing wells-reservoir and well-to-well connectivity. Indeed these connectivity properties usually depend on the fault network realization and may be strongly correlated with the reservoir flow dynamics. Connectivity analyses were performed on a fractured reservoir model involving a five-spot well configuration with four injectors and one producer. The connectivity was estimated from shortest path algorithms applied on a graph representation of the reservoir model. Several reservoir simulations were performed for different fault network realizations to seek correlations between injector-producer connectivity and water breakthrough time. The impact of the fracture properties uncertainties on the wells-reservoir connectivity was estimated via the cumulated connected volume computed for each well. This connectivity measure provides a mean to characterize and classify fault network realizations. Correlations were found between the water breakthrough time and the injector-producer connectivity, thus allowing one to identify the most probable fault network realizations to match the observed water breakthrough time. Finally, for a given fault network realization, it is shown how the oil recovery can be optimized by correlating injectors rates with the injector-producer connectivity. A gain of 3.106 m3 in produced oil was obtained, while retarding the water breakthrough time by 16 years, compared with a case where all injectors have the same rate. The proposed methodology and tools facilitate the history-matching of fractured reservoir, providing consistent reservoir models that can be used for production forecast and optimization.
Coupled Static/Dynamic Modeling For Improved Uncertainty Handling
Authors: Kaleta Malgorzata , van Essen Gijs , Van Doren Jorn , Bennett Richard , van Beest Bertwim , Van Den Hoek Paul , Brint John , Woodhead Tim 
Published: June 2012

Abstract
In the petroleum industry, history-matched reservoir models are used to aid the field development decision-making process. Traditionally, models have been history-matched by reservoir engineers in the dynamic domain only. Ideally, if any changes are required to static parameters as result of history matching the dynamic model, then these should be reflected directly in the static reservoir model, ensuring consistency between the static and dynamic domain. In addition, static model uncertainties are often not evaluated in the dynamic domain, which can result in the detailed modeling of geological features that have little impact on the dynamic behavior of the reservoir or the resulting development decision.
This paper demonstrates a workflow where the reservoir simulator and static modeling package are closely linked to promote a more integrated approach to reservoir model construction, facilitating the interaction between subsurface disciplines. Using either the reservoir simulator or the static modeling package as the platform, the output of the workflow is a sensitivity analysis of the uncertainties related to structure, rock properties, fluids and rock-fluid interactions. Computer-assisted history matching methods (i.e. adjoint-based and Design of Experiments) are used to find the parameter values that result in a history match model. The workflow is described for both a synthetic model and also a reservoir model from a real field case.
This methodology results in improved history-matched models and a better understanding of the static and dynamic subsurface uncertainties and their importance, leading to more informed decision-making. Furthermore, it is anticipated that it will result in faster accomplishment of the history matching studies.
The method presented here can significantly enhance the understanding of the impact of both static and dynamic subsurface uncertainties on development decisions. In addition, it offers a platform where all subsurface professionals involved in reservoir model construction and simulation can more optimally focus their efforts on improving the integrated understanding of their reservoirs.
Complexity of Wettability Analysis in Heterogeneous Carbonate Rocks, A Case Study
Authors: Mohammadlou Mohammadhossein , Mørk Mai Britt 
Published: June 2012

Abstract
Estimation of reservoir wettability and its effect on reservoir fluid flow, hydrocarbon recovery and fluid distribution has been the subject of many researches in recent years and remains one of the major challenges in reservoir characterization. This study examines the reservoir wettability in heterogeneous karstified carbonate rocks from comparison of special core analysis (SCAL) and resistivity index measurements on the core plugs, together with study of nuclear magnetic resonance (NMR) log, and formation pressure obtained by modular dynamic tool (MDT) measurements in the reservoir.
The SCAL test results present moderately water-wet reservoir conditions at the cored intervals of the reservoir. Surveys from resistivity index measurements are in general agreement with the SCAL results. Due to lack of core data in the lower/main part of the reservoir, analysis of the NMR T2 distribution are combined with MDT data to describe the reservoir wettability. The pressure data suggests a water gradient through the reservoir column except for anomalous high pressure values in which corresponds to zones with high resistivity and oil saturations. High oil saturation is not expected in zones where the reservoir has been water flooded (water level rise in the reservoir) after hydrocarbon accumulation. The study of the T2 distribution of these intervals helps to identify the oil wet nature of the larger pores in the reservoir. The surface relaxivity of oil when it wets the pore surface cause a shift in the T2 distribution towards shorter T2sC". The water volume, then, in oil wet pores relaxes as bulk relaxation with longer T2 compared to the water wet case. This study suggest that a combination of the NMR log with MDT data and resistivity logs provides a method to identify wettability characteristics of complex rocks when core plugs are missing.
Optimizing Well Placement With Quality Maps Derived From Multi-fidelity Meta-models
Authors: Le Ravalec Mickaele 
Published: June 2012

Abstract
Quality maps have been introduced as an efficient and expedient tool to select infill well placements, quality being a measure of how good an area is expected to be for production. Even though this tool is less CPU-time consuming than optimization algorithms, it still requires a significant number of flow simulations. Solving the computation time problem is even more challenging when dealing with geological uncertainty. In this case, quality maps have to be determined for several possible reservoir models, which clearly induces an increase in the number of flow simulations to be performed. In this paper, we first investigate the impact of geological uncertainty on quality maps. Then, we compare the potential of kriging and multi-fidelity meta-models for approximating quality from a reduced number of flow simulations. The main interest of the multi-fidelity technique is its ability to incorporate data at different levels of resolution. Thus, you can balance the flow simulations performed at the fine scale by flow simulations at the coarse scale. The latter being cheaper to evaluate, the computational overburden is considerably reduced. This approach turns out to be promising for the case studied.
In-Well, Optical, Strain-Based Flow Measurement Technology and Its Applications
Authors: Ünalmis Ö. Haldun , Trehan Sumeet 
Published: June 2012

Abstract
In-well flow measurement remains as one of the most difficult tasks in the oil and gas industry, mainly due to the challenging conditions of the downhole environment. When made successfully, however, it plays a major role in monitoring and optimizing well performance, especially for the wells equipped with advanced completion devices. The increasing demand for in-well flow measurement is also driven by other factors including zonal production allocation in multizone completions as well as reliable commingled production, reduction of surface well tests and facilities, and detection of production anomalies.
This paper provides a closer look at one of the state-of-art in-well flow measurement technologies: optical, strain-based, phase flow rate measurements via turbulent structure velocity and sound speed of the turbulent flow. It is an introduction to how this flow measurement technology works and how it is applied to different flow applications from single-phase injectors to multiphase producers. Specific field examples representing different flow applications are also referenced to published material. The strong and weak points of the technology are explored, and in the process, an operation envelope is produced for the use of this technology. The system response to the presence of advanced completion devices are also discussed, guidelines are given, and recommendations are made based on field and lab tests.
Understanding a technology’s strong and weak points before implementation is essential to ensuring that informed and successful decisions can be made concerning its use for a given application. This process is often mutually beneficial to both operators and equipment manufacturers since collaborations can lead to advancement of technology and, as a result, provide even more reliable solutions.