Integration of 3D Seismic & Dynamic Data Improves Interpretation of Structural Features

Well tests are often used to investigate reservoir heterogeneities such as fractures, conductivity of faults, and matrix permeability. Attributing a measured pressure response to a particular geological feature is problematic, as many different solutions will fit the same pressure response. Data integration is the key to understanding well pressure transients and the underlying geology controlling them. A recently acquired and interpreted 3D seismic survey indicated the reservoir contained numerous strike slip faults. To reduce the uncertainty associated with reservoir characterization, a multidisciplinary team comprising of geophysicists, geologists and reservoir engineers selected an area of the reservoir to focus their efforts. The integration of the 3D seismic with dynamic data provides a possible means of validating the interpretation. Anomalous transient pressure data were identified on five wells. Initial interpretations proved ambiguous with several possible geological reasons. Close examination of the 3D seismic data indicated in each case the presence of a fault. Faults were found to be the likely structural anomalies that have been detected by seismic and well test data. The fault throw, conductivity and its distance to the wellbore were estimated. The transient pressure data enabled us to evaluate the faults as sealing. Once the integration perception was adopted, and high quality data became available, concerns with the 3D seismic interpretation data and the uncertainties associated with pressure transient data that were initially ambiguous began to make sense.

This paper describes the full cycle of 4D seismic data integration comprised of workflows related to 4D data analysis, quality control of reservoir models and reservoir model updating using both 4D seismic and well production data. These workflows are applied to a deepwater field, where high quality 4D seismic data is available. In the first step, we analyze 4D seismic data and extract multiple attributes to image changes in reservoir properties. Next, we apply different workflows which link 4D seismic data with the reservoir model. Finally, we update the reservoir model automatically by simultaneously honoring the 4D seismic and well production data. We use a novel approach which incorporates 4D seismic amplitude differences without explicitly modeling the full physics in a joint history matching workflow. Introduction Reservoir monitoring using 4D seismic data is becoming an increasingly important tool for reservoir management (Calvert, 2005). Nevertheless, the quantitative integration of both 4D seismic and historical production data into reservoir simulation models is a challenging task, which recently has become an active direction of research. Huang et al. (1997) applied a stochastic optimization method to minimize the mismatch between synthetic and observed seismic data over a reservoir to achieve simultaneous history-matching of 4D seismic and well-by-well production data. Landa (1997) proposed a gradient-based method to integrate both 4D seismic and pressure transient data. Stephen et al. (2006) developed a workflow for multiple-model history matching through simultaneous comparison of spatial information extracted from 4D seismic data as well as individual well-production data. Employing the Neigbourhood Algorithm (NA) as the sampling engine this workflow was applied to the North Sea Schiehallion field. Skjervheim et al. (2007) presented a version of the Ensemble Kalman Filter (EnKF) for continuous model updating capable to match a combination of production and 4D seismic data. They tested the method on a synthetic case and a North Sea field case. Jin et al. (2007, 2008) proposed the combination of the Very Fast Simulated Annealing (VFSA) method with pilot-point parameterization to solve the 4D seismic history-matching inverse problem and applied the workflow to a synthetic case. Castro (2006) proposed a probabilistic approach to perturb a high-resolution 3D geocellular model for integrating data from diverse sources, such as well logs, geological information, 3D/4D seismic, and production data. This workflow was successfully applied on a reservoir of the Oseberg field. Jin et al. (2011) also proposed a flood front based 4D seismic history matching workflow. In this paper, we present a case study of the full cycle of 4D seismic data integration ranging from basic and qualitative 4D attribute analysis to the advanced 4D seismic history matching workflow. 4D seismic attributes analysis This workflow provides an analysis of 4D seismic differences related to changes in reservoir properties. First, timeshifts between baseline and monitor 3D seismic volumes are computed through cross-correlation. Some initial data preparation usually takes place before the cross-correlation of the datasets, including automatic gain control and trace stacking for signal to noise ratio enhancement. Next, the computed timeshift is removed from the monitor survey in order to obtain meaningful 4D difference attributes. At that point, 4D seismic attributes can be extracted from a given gate around time horizons of interest - usually reservoir tops. For reservoirs with large lateral thickness change, top and base reservoir horizons should be used for attribute calculation. Different types of attributes can be extracted, such as the root mean square (RMS), the normalized RMS difference (NRMSD), etc.

One of the main challenges in the execution of regional studies is the integration of large amounts of data coming from different sources and different disciplines. Even within the geophysical domain, integration of thousands of 2D seismic lines and dozens of 3D seismic volumes is a very demanding task. The aim of this paper is to provide a description on the use of fast track methodologies for the integration of 3D and 2D seismic data at country level for regional studies. This approach relies on a pragmatic way of merging seismic, processing data as point sets instead of traces, providing the flexibility of handling seismic information inside the geomodelling and geostatistical domain, where a grid of points can be resampled, reoriented, and ultimately merged into any desired geometry and resolution. The technical challenges include different spatial sampling, grid orientations, frequency contents and event timings. A preconditioning step has been included in the workflow in order to homogenize the data into a common ground, addressing compatibility issues of the different vintages through amplitude scaling, noise reduction and frequency balancing. Merging in a practical approach different 2D/3D seismic data sets into a single volume reduces drastically the amount of time spent in the data analysis and interpretation of geological features at regional scale. In this case of study, the workflow enables a feasible path for merging all seismic data acquired in Abu Dhabi over the past seven decades. The integrated volume helps geophysicists and geologists to carry out better seismic interpretations and perform proper structural analysis and prospect assessments. Finally, the seismic data has been integrated into a unique survey by interpolating the 2D and 3D seismic data to fill the gaps and generating a pseudo 3D survey at country scale. This regional scale single 3D seismic data allows better understanding of the geological and structural trends present in Abu Dhabi. This innovative approach offers a major advantage for regional data integration, expediting subsequent stages of seismic interpretation and description of the geological features at large scale for exploration assessments, prospect generation and 3D reservoir characterization.

Today, geostatistical reservoir characterization from 3D seismic volumes provides most static descriptions for reservoir models. These models can be improved by integrating the dynamic data in the reservoir description process. 3-D time-lapse seismic surveys have been proposed to relate time dependent-changes in seismic attributes to the flow processes in the reservoir. This paper presents a new approach to reservoir characterization by integrating time-lapse seismic and production data. The issues involved in the integration will be examined. A case study was conducted over a turbidite sheet sand reservoir in the Gulf of Mexico. Seismic data from the base survey were combined with log and production data to build an initial reservoir model which was run forward to the time of a second monitor seismic survey. Dynamic history matching by a simulated annealing type of optimization further improved the model. The output from this simulation was then converted to a synthetic monitor seismic survey using Gassmann's equations and a simple convolutional approach. A quantitative combined seismic and production history-matching methodology was then tested. It constrains the modeling process to match the production history and simultaneously minimize the differences between the synthetic and real 3-D seismic time-lapse data. This new systematic approach provides us with a quantitative time-lapse seismic analysis and reservoir characterization tool which has the potential to improve reservoir management. Introduction Once an oil reservoir has been found and is being produced, it is important to understand the movement of the fluid which is related to the flow mechanism and the reservoir heterogeneity. Recently, 3D seismic data have been used successfully to improve reservoir characterization by extraction of reservoir parameters using inversion, geostatistics and petrophysics to understand the coupling of seismic and rock properties. More than 10 years ago, laboratory work demonstrated that different fluid substitutions can cause acoustic changes, and time-lapse seismic was proposed to capture the changes in reservoir properties with time. These mostly qualitative studies showed that time-lapse seismic even on legacy data resulted in a better understanding of the production behavior of the reservoir. Time-lapse seismic data are mainly used for monitoring of the fluid movement in the reservoir. By integrating other data, they can provide another avenue for reservoir characterization not only including the fluid movement but also other reservoir properties. The following sections document a case study on a turbidite sheet sand reservoir in the Gulf of Mexico where 3-D time-lapse seismic data were integrated with production data from three wells over five years to characterize the reservoir by optimization, and time lapse seismic data were used to validate a seismic history matching methodology. Background This study uses two volumes of "off-the-shelf" data for timelapse seismic analysis. The base 3D seismic volume was acquired in 1988 before the production of the reservoir, while the monitor 3D seismic volume was acquired in 1994 after more than 5 years of production. The difference in orientation of the two surveys was small. The acquisition parameters were different for the two volumes. The base survey was reprocessed to improve the imaging part of the processing sequence to match the 1994 processing sequence more closely. Both volumes were processed through deterministic and adaptive deconvolution, 3-D dip move out and one-pass 3-D migration. The monitor volume was interpolated to smaller bins before migration. The limitations in using "off-the-shelf" data are well known and were recently discussed by Beasley et al., 1996. Since the focus of the present study is to demonstrate an improved seismic history matching methodology, it was decided to use legacy data rather than data reprocessed from field tapes to minimize differences. The accuracy of the results is expected to improve when using carefully reprocessed data sets. The case study was conducted over a sheet sand reservoir in the Gulf of Mexico, offshore Lousiana. The sand is of Pliocene age and pinches out onto a salt-related structural high that controlled its deposition. The average porosity is about 31 % and its permeability is about 500 md. P. 439^

VeritasDGC. Summary We present a new approach to the simultaneous pre-stack inversion of PP and, optionally, PS angle gathers for the estimation of P-impedance, S-impedance and density. Our algorithm is based on three assumptions. The first is that the linearized approximation for reflectivity holds. The second is that PP and PS reflectivity as a function of angle can be given by the Aki-Richards equations (Aki and Richards, 2002). The third is that there is a linear relationship between the logarithm of P-impedance and both S-impedance and density. Given these three assumptions, we show how a final estimate of Pimpedance, S-impedance and density can be found by perturbing an initial P-impedance model. After a description of the algorithm, we then apply our method to both model and real data sets.

Some difficulties are frequently associated with the integration of seismic and flow simulation datasets, especially related with the low vertical resolution of the seismic data and the uncertain estimations in the areas between the wells. One challenge is then the integration of both datasets in different scales, in order to take advantage of their characteristics. The present study proposes a redistribution of the reservoir saturation estimated with 4D seismic inversion methods, combining the information provided by the flow simulation in order to improve the quality of the estimations and their resolution. The methodology comprehends a saturation redistribution algorithm that is applied to each reservoir block combining the information of two saturation maps: one derived from the 4D seismic data and the other estimated by the flow simulator. The final saturation estimation follows the vertical distribution given by the simulation data but keep the average behavior observed in the 4D seismic. In order to have a better control of the results, the methodology is applied to a synthetic dataset that includes a reservoir model with different grid resolutions: geomodel, simulation model and seismic model. Two different case studies present the main results of the proposed methodology to improve the saturation predictions. The first case study represents an ideal solution being assumed that the base model (simulation model) is very similar to the reference model (geomodel that represents the true answer), remaining a few differences due to the different scales. In the second case study, the base model is selected between multiple realizations during the uncertainty reduction process. The results shows that is possible to improve the resolution of the saturation variation maps computed from 4D seismic data allowing the identification of new fine scale heterogeneities and providing better estimations of the saturation changes due to production. This methodology can also give additional clues in future history matching procedures through the identification of critical regions. With the continuous calibration of the models during a history matching process the results obtained with the redistribution method tend to improve, approaching the results obtained in the first case study. The proposed redistribution method combines the best characteristics of the seismic and simulation data. It includes the higher sensibility of the seismic data to identify the areal distribution of the main anomalies and inserts the higher sensibility of the simulation data regarding the identification of vertical water flow trends due to gravitational effects. Thus, the procedure introduces, in the maps provided by 4D seismic, new information regarding the injection/production patterns that become more and more reliable as we approach the wells.

An Upper Cretaceous carbonate reservoir, onshore oil field in Abu Dhabi is characterized by its vigorous surface topography and subsurface complex structural setting. The studied reservoir is a highly fractured elongated anticline trending NE-SW. Fracture occurrence and distribution have influenced the reservoir performance in terms of oil production and water cut from the field. Seismic attributes integrated with well log data and well performance have provided a good understanding of the lineament/fracture distribution within the reservoir. In addition, this integration enhanced the Full Field Development Plan (FFDP) optimization in terms of well placement and reservoir performance to avoid early water break through (EWBT) due to fractures. 3D seismic data was acquired with high fold and wide azimuth over the field in 2007. The 3D seismic data was processed in 2008 with some processing issues. In 2012, new algorithms were applied over a pilot area in order to resolve the processing issues and to preserve relative true amplitude for further reservoir characterization purposes. The pilot products have better identified short falls in the 2008 processed data. Seismic attributes were analyzed and the interpreted lineaments/fractures distribution will help better understand fracture orientation and their impact on oil production and water cut for full field development. The Seismic attributes successfully captured additional information and guided the well planning to avoid the highly lineament/fractured area. In addition, the new identified fracture system provides essential information for the ongoing and future development plans for this field. This 3D seismic input for fracture detection and well trajectories optimization resulted in better well performance and delay of water production especially in mid flank wells. The preliminary results of the attribute extraction at the reservoir targets are encouraging and new 3D seismic reprocessing data is considered a potential solution for the quantitative seismic interpretation and the reservoir characterization which achieved optimum well locations and orientation in this complicated onshore field.

Summary Elastic seismic inversion is a tool frequently used in analysis of seismic data. Elastic inversion relies on a simplified seismic model and generally produces 3D cubes for compressional-wave velocity, shear-wave velocity, and density. By applying rock-physics theory, such volumes may be interpreted in terms of lithology and fluid properties. Understanding the robustness of forward and inverse techniques is important when deciding the amount of information carried by seismic data. This paper suggests a simple method to update a reservoir characterization by comparing 4D-seismic data with flow simulations on an existing characterization conditioned on the base-survey data. The ability to use results from a 4D-seismic survey in reservoir characterization depends on several aspects. To investigate this, a loop that performs independent forward seismic modeling and elastic inversion at two time stages has been established. In the workflow, a synthetic reservoir is generated from which data are extracted. The task is to reconstruct the reservoir on the basis of these data. By working on a realistic synthetic reservoir, full knowledge of the reservoir characteristics is achieved. This makes the evaluation of the questions regarding the fundamental dependency between the seismic and petrophysical domains stronger. The synthetic reservoir is an ideal case, where properties are known to an accuracy never achieved in an applied situation. It can therefore be used to investigate the theoretical limitations of the information content in the seismic data. The deviations in water and oil production between the reference and predicted reservoir were significantly decreased by use of 4D-seismic data in addition to the 3D inverted elastic parameters. Introduction It is well known that the information in seismic data is limited by the bandwidth of the seismic signal. 4D seismics give information on the changes between base and monitor surveys and are consequently an important source of information regarding the principal flow in a reservoir. Because of its limited resolution, the presence of a thin thief zone can be observed only as a consequence of flow, and the exact location will not be found directly. This paper addresses the question of how much information there is in the seismic data, and how this information can be used to update the model for petrophysical reservoir parameters. Several methods for incorporating 4D-seismic data in the reservoir-characterization workflow for improving history matching have been proposed earlier. The 4D-seismic data and the corresponding production data are not on the same scale, but they need to be combined. Huang et al. (1997) proposed a simulated annealing method for conditioning these data, while Lumley and Behrens (1997) describe a workflow loop in which the 4D-seismic data are compared with those computed from the reservoir model. Gosselin et al. (2003) give a short overview of the use of 4D-seismic data in reservoir characterization and propose using gradient-based methods for history matching the reservoir model on seismic and production data. Vasco et al. (2004) show that 4D data contain information of large-scale reservoir-permeability variations, and they illustrate this in a Gulf of Mexico example.

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This paper proposes a method for quantitative integration of seismic (elastic) anisotropy attributes with reservoir performance data as an aid in characterization of systems of natural fractures in hydrocarbon reservoirs. This method is demonstrated through application to history matching of reservoir performance using synthetic test cases. Discrete Feature Network (DFN) modeling (Dershowitz et al.1) is a powerful tool for developing field-wide stochastic realizations of fracture networks in petroleum reservoirs. Such models are typically well conditioned in the vicinity of the wellbore through incorporation of core data, borehole imagery, and pressure transient data. Model uncertainty generally increases with distance from the borehole. Threedimensional seismic data provides uncalibrated information throughout the inter-well space. Some elementary seismic attributes such as horizon curvature and impedance anomalies have been used to guide estimates of fracture trend and intensity (P32) (Dershowitz and Herda2) in DFN modeling through geostatistical calibration with borehole and other data. However, these attributes often provide only weak statistical correlation with fracture system characteristics. The presence of a system of natural fractures in a reservoir induces elastic anisotropy that can be observed in seismic data. Elastic attributes such as azimuthally dependent normal moveout velocity (ANMO), reflection amplitude versus azimuth (AVAZ), and shear wave bi-refringence can be inverted from 3D seismic data. Anisotropic elastic theory provides physical relationships among these attributes and fracture system properties such as trend and intensity. Effective elastic media models allow forward modeling of elastic properties for fractured media. A technique has been developed in which both reservoir performance data and seismic anisotropic attributes are used in an objective function for gradient-based optimization of selected fracture system parameters. The proposed integration method involves parallel workflows for effective elastic and effective permeability media modeling from an initial DFN estimate of the fracture system. The objective function is minimized through systematic updates of selected fracture population parameters. Synthetic data cases show that 3D seismic attributes contribute significantly to reduction of ambiguity in estimates of fracture system characteristics in the inter-well rock mass. The method will benefit enhanced oil recovery (EOR) program planning and management, optimization of horizontal well trajectory and completion design, and borehole stability studies.

Seismic data incorporation in reservoir simulation models history matching (HM) studies has been continuously growing. 4D seismic data, in contrast with well production data, can provide a very good scenario of fluids arrangement along reservoir. In this work we describe how 3D and 4D seismic data gathered in acquisitions performed in Campos Basin was incorporated in Marlim Sul deep water field geological model reconstruction and in assisted HM (AHM). It is taken advantage of both 3D and 4D seismic data in several stages of the study, for instance, in the construction of a new porosity – most influential in impedance – model by using a methodology based on the inversion of synthetic seismic (calculated by petro-elastic model) in porosity through an optimization process that aims to reduce the difference between observed and synthetic impedance, and when defining influential parameters based on fluids displacement registered by seismic signal, by using a technique based on the creation of transmissibility multipliers parameters regions that considers the fluids displacement shown in 4D signal. Another relevant point is the use of information from reservoir and 3D seismic data when weighting the 4D data in the objective function. Combining the above mentioned techniques with the knowledge of the field – supported by the 3D seismic data – which allowed, for instance, identification of faults – where fault transmissibility multipliers were used as parameters in the HM process – a fairly good agreement on the observed well and seismic production data was achieved. HM studies using AHM tools have been shown a much more time-efficient technique when compared to manual HM. The incorporation of 4D seismic data can considerably improve the HM quality by improving the reservoir description, once it increases the ability of describing fluids arrangement and pressure distribution. The techniques successfully applied in the Marlim Sul field HM support these conclusions.

One of the challenging issues of using 4D seismic data into reservoir history matching is to compare the measured data to the model data in a consistent way. It is important to decide which kind of seismic data can be best used and at which level of history matching process they can be integrated. In this work, we have performed 4D seismic history matching of a sector model based on a North sea reservoir in the ensemble Kalman filter (EnKF) framework and have investigated the effects of different types of time-difference seismic data to update reservoir models. The reservoir-seismic model system consists of a commercial reservoir simulator coupled to an implemented rock physics model and a forward seismic modeling tool based on 1D convolution with weak contrast reflectivity approximation. The objective of this work is to investigate the sensitivity of different combinations of production and seismic data on EnKF model updating. The uncertain static reservoir parameters considered are porosity and permeability; dynamic variables such as pressure and water saturation are conditioned to both production and seismic data. In particular, we are interested to quantify the performance of the wells; also to match seismic data and to estimate the reservoir parameters. In most of the cases of reservoir characterization, time-difference impedance data performed better than time-difference amplitude data and considerably reduced posterior ensemble spread. The matching of seismic data generally improved with the inclusion of time-difference seismic data. In estimating posterior porosity and permeability, seismic difference data provided better estimate than using only production data, especially in aquifer region and also in areas that might be considered for in-fill wells. Thus, in our realistic synthetic case based on a full field reservoir model, we experienced that the integration of seismic data in the elastic domain provided better performance than using amplitude data. In addition, we investigated the effects of vertical resolution of seismic data on EnKF model updating, and showed that the choice of wavelet discretization points can have significant influence on the quality of history matching.

Summary Volumetric maximum curvature attribute computed from 3D ocean bottom cable (OBC) seismic data, production logging tool (PLT), inorganic chemical tracer data, and fractures observed from core and full-bore formation microimager (FMI) logs were integrated to characterize fractured carbonate reservoirs of an offshore oil field in Abu Dhabi, United Arab Emirates (UAE). The extracted maximum curvature anomalies are predominantly orientated in NNE-SSW and NE-SW, a trend perpendicular to the dominant fault direction in the oil field and similar to the dominant strike directions of fractures measured from core data and FMI logs. Because the fracture strike directions of well data mimic the strike directions of curvature anomalies at corresponding reservoir levels, we interpreted the maximum curvature anomalies to represent dilatational fractured zones or fracture corridors. Integration of dynamic data, such as PLT and chemical tracers, and maximum curvature anomalies demonstrate that the inferred fracture zones can determine water breakthroughs as well as inter- and intrareservoir communications. As a result, this study highlights possible fracture zones and their internal architecture, as well as their potential flow capabilities. These results play a key role in reservoir management and monitoring of water movement through structural pathways.

In some oilfields with 3D seismic data, the deeper structure cannot be observed due to poor quality deep seismic data. Layer stripping using both seismic and gravity data is a solution for this problem but it cannot get satisfactory results because the horizontal variations in formation density are ignored. We present a variable-density formation separation technique to address this problem. Based on 3D seismic depth data and laterally-variable density derived from 3D seismic velocity data, the upper formation gravity effect is calculated by forward modeling and removed from the Bouguer gravity. The formation-separated gravity anomaly with variable density is obtained, which mainly reflects the deeper geological structure. In block XX of North Africa, the shallow formations seismic data is excellent but the data at the top of basement is poor. The formation-separated gravity anomaly processed under the control of 3D seismic data fits well with the known seismic interpretation and wells. It makes the geological interpretation more reliable.

The Late Jurassic Najmah Formation of Northeast Kuwait consists of a fractured tight carbonate reservoir and organic-rich kerogen layer (Figure 1). Development of the Najmah reservoir is contingent on recognizing naturally fractured areas. Prior to seismic reservoir characterization, it is essential to ensure that the data quality is reliable before extracting any information from the seismic data. Noise contamination can obscure the reflections of interest, leading to inaccurate interpretation and the need for further data analysis for reservoir delineation. Data acquired in the study area indicates that P-wave seismic data within the reservoir interval suffers from the interference of coherent noise related to the interbed multiple. The interbed multiple is a serious problem that is common in the land seismic datasets in the Middle East (Al-Khaled et al., 2008; Al-Nahhas et al., 2008; El-Emam et al., 2011, 2005; Lesnikov and Owusu, 2011; Ras et al., 2012; Sonika et al., 2012; Wu et al. 2011). This study utilized a 9 mile2 (23.3 km2) 3D full azimuth P-wave seismic data set provided by Kuwait Oil Company (KOC) to the Reservoir Characterization Project (RCP) at the Colorado School of Mines. The seismic data was a preliminary result of pre-stack time migration from continuing seismic data processing. Short and long period demultiple and interbed demultiples were applied during the original data processing. A synthetic seismogram of well B portrays the reservoir interval with greater amplitude than the seismic data (Figure 2). This anomaly is consistently observed for all seismic well ties of ten available wells within the 3D seismic data. Furthermore, inside-outside corridor stack analysis of zero-offset VSP (Vertical Seismic Profile) depicts similar amplitude difference that indicates the presence of noise interference from multipathing of seismic energy above the reservoir interval. Evidence of the presence of multiples can be observed from the raw stack of down-going wavefields of the zero-offset VSP. Interbed multiple effects on the seismic data can be seen as a periodic repetition of reflection events, either individual events or interference with primaries. In this case, the multiples seem to interfere with the primary reflection. This study reveals interbed multiples related to the first anhydrite layer within the Gotnia Formation above the reservoir layers are the primary cause of the interference. Applying model-based interbed multiple attenuation reduces the noise interference and improves the imaging of the reservoir section. The multiple-attenuated seismic data have a better correlation with synthetics derived from ten control wells used in this study, leading to better seismic inversion accuracy and reservoir characterization.