127 research outputs found
From basin to reservoir models: an integrated workflow
No full textReservoir geological modeling encompasses all the aspects related to the definition of the structural, stratigraphic, lithological and petrophysical features of the mineralized rock volume, leading to the estimation of the spatial distribution and of the total amount of stored hydrocarbons.
Reservoir models typically result from the quantitative integration of well and seismic data through geostatistical tools. Based on such models, equiprobable realizations of structural settings and property distributions can be generated by appropriate stochastic simulation techniques. On the contrary, the integration of regional (or basin) scale information is commonly performed in a qualitative or semi-quantitative way, for example through the definition of regional property trends. This qualitative or semi-quantitative approach can strongly limit the assessment of the impact of the uncertainties associated with the regional knowledge on the overall uncertainty affecting the reservoir model.
In order to overcome the limits of the traditional methodologies a different approach is here proposed, which leads to the quantitative integration of the typical dataset for a reservoir geological model (including well and seismic data) with the parameters estimated by a quantitative dynamic sequence stratigraphic model.
The proposed quantitative approach could significantly improve the capability to predict the 3D facies distribution and architecture and the lithological fraction of the hydrocarbon-bearing rocks, i.e., sand fraction in a shaley/clayey environment. These features are well known to be crucial during the appraisal phase of the reservoir when relevant decisions have to be taken but few wells are drilled and volumetric estimates are performed with a limited amount of available data. Furthermore, a proper prediction of the 3D facies architecture might be very effective when planning the location of new wells or infilling wells.
The application of a deterministic model (SimClast, by Delft University of Technology) is suggested to generated a 3D facies distribution and architecture at the regional scale. A reasonable range of uncertainty affecting the input parameters should be assumed to account for actual interpretation uncertainties. A geostatistical approach is then conceived to transfer the facies architecture at the reservoir scale through the integration of the available geological and geophysical data, such as well logs and seismic surfaces.
Key properties at specified locations surrounding the reservoir volume which serve as boundary conditions for the reservoir models can be defined with the aid of 3-D process-based stratigraphic modeling. In this way, reservoir models can be constrained to maintain quantitative coherence with the large-scale geological setting defined by the basin-scale model and the uncertainty associated with each key basin property can be propagated all the way to reserve estimation. This approach provides a rigorous assessment of the information content of all data sources which may be used to guide further data-acquisition campaigns.
The impact of the quantitative integration of basin-scale derived boundary conditions on reservoir models has been evaluated through the application of the new workflow to a synthetic case study. In particular, the workflow was applied to a fluvio-deltaic environment so as to evaluate the uncertainty reduction in the description of a facies distribution at the reservoir scale by constraining stochastic simulations to basin-derived boundary conditions. The impact of the uncertainty affecting the model input parameters (sediment entry point, sea level and initial topography) on the stratigraphic setting and channels distribution at the basin scale was investigated; furthermore, a Bayesian approach for uncertainty reduction at the basin scale was introduced by application of a likelihood function comparing each simulated scenario with the available dataset. This approach was conceived for application to real cases where the typical dataset consists of well and seismic data. Eventually, the uncertainty at the reservoir scale was evaluated by constructing sand probability curves at specified reservoir locations.
The comparison with the classical procedure highlighted that the main advantage arising from the integration of basin data in reservoir modeling is an improved predictability of channel occurrence.
In the basin unconstrained case the predictability of the facies architecture is null. In the constrained cases a significant vertical variability of the sand probability curve is observed, thus the channel location can actually be predicted. Furthermore, in the proposed methodology channels and floodplain occurrence are statistically preserved both as global fractions and local position. The reduction of the uncertainty of the environmental input parameters at the basin scale by application of a likelihood function significantly improves the predictability of the facies distribution at the reservoir scale. The analysis of the facies sequence at the monitoring points indicated that more precise and accurate estimates are obtained if the uncertainty is reduced by the application of the likelihood function
Pseudo-Elastic Response of Gas Bearing Clastic Formations: An Italian Case Study
No full textThe research presented in this paper focuses on the analysis of land movements induced by underground gas storage operations in a depleted reservoir in Northern Italy with the aim of increasing the understanding of the deformation response of deep formations via a real case study. The a priori knowledge of the pseudo-elastic parameters showed a substantial discrepancy between static values from triaxial lab tests and dynamic values obtained via the interpretation of sonic data at wellbore scale. The discrepancy is not surprising for the formations under investigation: A thousand meters of a silty to shaly sequence intercalated with arenaceous banks above a reservoir formation, which is basically made up of sandstone intercalated with shale intervals and conglomerates. Information collected for over more than ten years of seasonal production/injection cycles (i.e., time and space evolution of the reservoir fluid pressure and of the induced land surface movements) was then combined in a 3D numerical geomechanical model to constrain and update the a priori knowledge on the pseudo elastic model parameters via a back analysis approach. The obtained calibrated model will then be used for reliable prediction of system safety analyses, for example in terms of induced ground movements
Capturing channelized reservoir connectivity uncertainty with amalgamation curves
No full textDuring reservoir characterization all the geological uncertainties affecting the quantity and distribution of hydrocarbons should be captured to assess the risks affecting final recovery. In a typical modeling workflow the geological uncertainties are accounted for through the construction of a sufficiently large set of 3-D static models. Out of this set, a few representative models are selected and dynamically simulated so as to correlate the geological characteristics of the reservoir with its dynamic performance and to propagate the uncertainty onto the final recovery factors yet maintaining the computational run time acceptable. In channelized depositional environments, which are strongly heterogeneous, the selection approach must also account for channel connectivity, which plays a key role in the possibility of efficiently draining the reservoir for a reasonable number of wells. This study can be seen as a step forward in the assessment of the risks associated to the development of channelized reservoirs under the assumption that a way to express the concept of channel connectivity is channel amalgamation. Channel amalgamation is here defined through amalgamation curves which are numerically described using a set of indexes whose combination provide spatial information of channel intersections. These indexes were calculated for a full set of 3-D geological models and used to steer the selection of a representative model sub-set for subsequent fluid flow simulations. The validity of the index-based selection was verified on different sets of synthetic reservoir models through the evaluation of the representativeness of the model sub-set in reproducing the uncertainty of the original dataset. Eventually, the existence of a strong correlation between channel amalgamation and production performance was proved. From a practical perspective, the possibility to include channel amalgamation in the assessment of the geological models can considerably improve the representativeness of the selected models for uncertainty propagation thus reducing significantly the number of geological models to be considered
Artisti industriosi e speculativi : Paolo Morigia e il Quinto Libro della «Nobiltà di Milano»
No full textIl titolo di questo libro, Artisti industriosi e speculativi, riprende le parole spese da Paolo Morigia (1525-1604) per definire gli artisti attivi a Milano alla fine del Cinquecento nel Quinto Libro della sua Nobiltà di Milano (1595). Qui l’autore fissa in modo sbrigativo pittori, scultori e architetti cittadini e si estende invece sulle botteghe dei maestri che avevano trasformato Milano nella capitale del lusso europeo, animata da ricamatori, miniatori, intagliatori di pietre dure e cristalli, orafi, argentieri, armaioli, produttori prolifici (perciò industriosi) di invenzioni (perciò speculativi) destinate agli intenditori del tempo, come uomini di corte, di chiesa o collezionisti. Le notizie artistiche raccolte nella Nobiltà di Milano e in alcune opere di poco precedenti (come l’Historia dell’antichità di Milano, 1592) sono state subito utilizzate dagli eruditi delle generazioni successive, tanto che i testi di Paolo Morigia sono diventati miniere estrattive di informazioni scavate acriticamente. Per la prima volta, questo libro ricolloca Paolo Morigia al centro, ricostruendone la cultura religiosa (era un gesuato), i gusti artistici (indirizzati in primo luogo all’allestimento della chiesa milanese di San Gerolamo, oggi scomparsa) e le relazioni (per esempio con un ramo della famiglia Trivulzio, legato agli Asburgo); nella seconda parte presenta il commento e il ricontrollo delle notizie sugli artisti raccolte nel Quinto Libro della Nobiltà di Milano, cui fa seguire segue un’antologia che lo ripropone accanto ad altri testi utili a comprenderne la storia e lo sviluppo
TOWARDS PROCESS-BASED GEOLOGICAL RESERVOIR MODELLING: OBTAINING BASIN-SCALE CONSTRAINTS FROM SEISMIC AND WELL DATA
No full textForward stratigraphic modelling aims at representing the spatial distribution of lithology as a function of physical processes and environmental conditions at the time of deposition so as to integrate geological knowledge into the reservoir modelling workflow, thus increasing predictive capabilities of reservoir models and efficient exploitation of hydrocarbons. Application of process-based models in inverse mode is not yet well-established due to our limited insight into the information content of common subsurface data and the computational overhead involved. In this paper we examine inverse modelling of stratigraphy by using a typical dataset acquired in the hydrocarbon industry, which consists of seismic data and standard logs from a limited number of wells. The approach is based on the use of a forward model called SimClast, developed at Delft University of Technology, to generate facies distribution and architecture at the regional scale. Three different goodness of fit functions were proposed for model inversion, following an inference approach. A synthetic reservoir unit was used to investigate the impact of the uncertainty affecting the input parameters and the information content of seismic and well data. The case study showed that the model was more sensitive to the initial topography and to the location of the sediment entry point than to sea level. The depth of the seismic reflector corresponding to the top-reservoir surface was the most informative data source; the initial and boundary conditions of the simulation were constrained by evaluating the depth of this reflector across the whole basin area. In the reservoir area, where the seismic-to-well tie was established, the depth of the reservoir top does not give enough information for constraining the model parameters. Our results thus indicate that evaluation of basin-scale data permits reduction of uncertainty in (geostatistical) reservoir models relative to the current workflow, in which only local data are used. Effective use of well data to generate reservoir models conditioned to basin-scale scenarios requires post-processing methods to downscale the output of the forward model used in the experiment
Reducing the uncertainty of static reservoir models: Implementation of Basin-scale geological constraints
No full textWe propose a new workflow for building static reservoir models of siliciclastic fluvio-deltaic systems. The proposed strategy requires a process-based stratigraphic simulation model which incorporates a reservoir-scale alluvial architecture module nested within a low-resolution basin-scale (sequence-stratigraphic) model. The basin-scale model is run with the intent to approximate large-scale basin-fill properties (based on geological/geophysical background information about palaeotopography, sea level, sediment supply, subsidence, and so forth). Subsequently, the model may be stochastically optimised by dedicated post-processing software to mimic sub-grid (reservoir-scale) properties of selected parts of the basin fill. This approach allows us to narrow down the range of possible scenarios (realisations) from the outset, which results in more reliable uncertainty estimates associated with reservoir models. Pilot studies suggest that the improvement of geological credibility of stochastically simulated fluvial reservoir models may go hand-in-hand with a significant reduction of the computational effort of inverting basin-scale (process-based) stratigraphic forward models. The implementation of geological constraints on object-based models is expected to improve estimation of sand-body connectivity and dynamic reservoir behaviour, and will therefore contribute to reduction of the non-uniqueness in current static reservoir models. Furthermore, the uncertainty associated with each basin-scale parameter can be propagated all the way through to reserve estimation. The partitioning of the overall uncertainty into contributions at the basin and reservoir scales may be quantitatively assessed, and the information content of all available data may be quantified. Copyright 2013, Society of Petroleum Engineers
How to integrate basin-scale information into reservoir models
No full textObjectives and scope of the Study In this paper a new approach is presented to consistently integrate basin-scale information into reservoir models. The impact of the quantitative integration of boundary conditions derived from basin-scale modeling on the facies distribution at the reservoir scale is evaluated. To this purpose, a new workflow was defined based on a geostatistical approach. The aim was that of integrating the typical dataset for reservoir geological modeling, comprising well and seismic data, with a potentially new kind of data obtained from 3-D process-based stratigraphic modeling and related to the distribution of the hydrocarbon bearing volumes. Quantitative coherence between the small scale reservoir volume and the large-scale geological setting defined by the basin model was imposed. Synthetic case studies were set up to verify the effectiveness of the method.
Applications The entire process was applied to a fluvio-deltaic environment to integrate the basin-derived information, such as (1) the overall reservoir/non reservoir volumes, (2) the 3D distribution of channelized volumes and (3) related flow directions, to the reservoir model. Eventually, the uncertainty reduction in the description of the final facies distribution at the reservoir scale was evaluated.
Results, Observations and Conclusions The developed approach proved very efficient to estimate the lithological fraction of the hydrocarbon bearing rocks (i.e. sands in a shaley/clayey environment). The lithological fraction is of crucial importance during the appraisal phase of a reservoir when relevant decisions have to be taken but few wells are drilled and, as a consequence, a limited amount of data is available to perform a reliable volumetric estimate. Furthermore, the prediction of the 3D facies architecture (such as the channel pattern in a fluvial depositional environment) can effectively assist in the well planning strategy. Besides, the overall uncertainty affecting a reservoir model can be assessed; this uncertainty is both a function of the initial environmental parameters for basin modeling and of the adopted methodological approach for basin-to-reservoir data integration. Therefore, an accurate inference of the basin parameters is needed to achieve a reliable prediction of both the channel location and the sand/shales volumes fractions.
Significance of subject matter Reservoir modeling can significantly benefit from the integration of quantitative basin-scale information. In particular, the numerical modeling of the stratigraphic sequence can be used to steer the reconstruction of the reservoir internal geometry and to reduce the uncertainty in the distribution of the hydrocarbon-bearing lithologies. Furthermore, this approach provides a rigorous assessment of the information content of all the available data and thus it might be very useful to guide further data acquisition campaigns
Study of reservoir production uncertainty using channel amalgamation
No full textThe characterization of a reservoir's internal architecture is a major challenge, especially during the reservoir appraisal phase when the information is limited. At this stage, all the uncertainties affecting the quantity and distribution of hydrocarbons in the reservoir should be captured and accounted for in the evaluation of the final recovery to properly assess the viability of any development plan. A typical modeling workflow accounting for geological uncertainties consists in creating a large set of 3-D geological (static) models, selecting a few representative realizations out of this set based on the calculated hydrocarbons originally in place and simulating future production from the selected reservoir models for fixed well count and locations so as to propagate the uncertainty onto the final recovery factors. However, in channelized reservoirs connectivity plays a key role in the possibility of efficiently draining the reservoir with a reasonable number of wells, thus the subset of representative realizations should be selected not only based on the hydrocarbons originally in place but also based on the connectivity among the channels. To this end, an index quantifying the channel static connectivity was defined in the literature but it is demonstrated in this paper that this index fails to account for the internal architectural layout of the reservoir, namely amalgamation, which reflects the quality of the connectivity between channels. Thus, a new index is proposed by the authors to quantify channel amalgamation and steer the selection of representative geological models for subsequent fluid flow simulations. This new index was calculated for a series of synthetic channelized 3-D static models characterized by different degrees of channel sinuosity. Each model was then dynamically simulated under the same production constraints and the final hydrocarbon recovery was obtained. Eventually, the existence of a relation between channel amalgamation and production performance was assessed to prove the validity of the proposed index as a sampling criterion. The results confirmed that channel amalgamation, more than static connectivity, affects reservoir performance thus can be a better indicator to capture reservoir uncertainty. Nonetheless, the use of a global indicator still presents limits in the description of the internal geological setting of the reservoirs and this has implications in achieving an accurate selection of a subset of equiprobable models. Only by introducing information related to the spatial distribution of amalgamation these limits could be overcome in the futur
HOW TO APPROACH SUBSIDENCE EVALUATION FOR MARGINAL FIELDS: A CASE HISTORY
No full textThis paper presents the evaluation of the subsidence potentially induced by underground storage of natural gas in a marginal depleted field located in Southern Italy. The critical aspect of the study was the lack of data because economic and logistic reasons had restricted data acquisition at the regional scale to perform a geomechanical study. This limitation was overcome by accurately gathering the available data from public sources so that the geometry of a largescale 3D model could be defined and the formations properly characterized for rock deformation analysis. Well logs, seismic data and subsidence surveys at the regional scale, available in open databases and in the technical literature, were integrated with the available geological and fluid-flow information at the reservoir scale. First of all, a 3D geological model, at the regional scale, incorporating the existing model of the reservoir was developed to describe the key features of a large subsurface volume while preserving the detail of the storage reservoir. Then, a regional geomechanical model was set up for coupled mechanic and fluid-flow analyses. The stress and strain evolution and the associated subsidence induced in the reservoir and surrounding formations by historical primary production as well as future gas storage activities were investigated. Eventually, the obtained results were validated against the measurements of ground surface movements available from the technical literature for the area of interest, thus corroborating the choice of the most critical geomechanical parameters and relevant deformation properties of the rocks affecting subsidenc
Increasing the predictive power of geostatistical reservoir models by integration of geological constraints from stratigraphic forward modeling
No full textCurrent static reservoir models are created by quantitative integration of interpreted well and seismic data through geostatistical tools. In these models, equiprobable realizations of structural settings and property distributions can be generated by stochastic simulation techniques. The integration of regional (or basin) scale knowledge in reservoir models is typically performed qualitatively or semi-quantitatively (for example, through the definition of regional property trends or main channel-belt orientations). This limited use of regional information does not allow an assessment of the impact of the uncertainties associated with the regional knowledge on the overall uncertainty of the reservoir model. A novel approach is proposed in this study, which allows us to consistently integrate basin-scale information into reservoir models. A new type of data, related to the distribution of the potential hydrocarbon-bearing volumes at basin scale, was obtained from a 2-DH process-based stratigraphic forward model (SFM) and integrated as a soft constraint in the geostatistical reservoir modeling. As a consequence, reservoir models are quantitatively consistent with the large-scale geological setting defined by the SFM output. Furthermore, the uncertainty associated with each SFM parameter can be propagated to reserve estimation. Thus the partitioning of the overall uncertainty affecting a reservoir model into the contributions of the uncertainties at the basin and reservoir scales can be quantitatively assessed. Several synthetic case studies were carried out with and without conditioning to SFM output, which verified the effectiveness of the method. A logical next step is to apply the proposed methodology to a real-world case
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