A robust and detailed reservoir model is an essential requirement when a fast track approach drives the development of a green field. Such a tool can only be developed through the orchestration of Geological and Geophysical (G&G) and Reservoir Engineering disciplines. This integration effort is, first of all, aimed at identifying the key characteristics of the reservoir most impacting its dynamic behavior at different scale and, eventually, at capturing them with the proper modelling approach.
This paper decribes such approach to the case of a complex deep-water reservoir belonging to slope-toe of slope environment. A 3D integrated static model was built by incorporating core and log data, their petrophysical interpretation, a description of the depositional and architectural elements, a quantitative seismic reservoir characterization and the few dynamic information available at this early development stage.
The implemented geomodeling workflow focused on heterogenetiy that could affect reservoir performance such as structural-stratigraphic discontinuities that could act as hydraulic barriers. Facies in the interwell space were distributed by applying seismic-derived 3D trends. Facies distribution eventually provided the framework within which petrophysical properties modelling was performed. During the implementation of this integrated G&G and Reservoir workflow, continuous crosschecks of consistency and robustness of the model led to elaborate the final product.
The resulting reservoir model captured critical uncertainties (e.g. degree of reservoir heterogeneity including stratigraphic discontinuities) leading to an optimized development scheme, that allowed to minimize risks, despite the few data available.
The reservoir quality prediction is carried out at the exploration scale through software that try to model the diagenetic evolution of the reservoir. The input data are quantitative petrographic data, core analysis results and the burial and thermal history of the wells either 1D or 3D (PSM). The procedure starts from the calibration of the model on a well with cores or sidewall cores for petrographic-diagenetic data and RCA and with a calibrated burial and thermal history. Once calibrated, the model extends to the whole area of interest following the 3D burial and thermal history model of the reservoir. The extension of the approach to the reservoir scale requires a dedicated workflow that comprises the following points: - Identification of the main diagenetic issues from petrographic studies; - Use of the information coming from logs of the non-cored wells in a diagenetic perspective; this step comprehends the realization of detailed CPI of wells and, if necessary, additional mineralogical analyses in order to fix a valuable mineralogical model; - 3D burial and thermal history reconstruction at the reservoir model scale using the reservoir model surfaces; the step implies the reconciliation of the regional explorative model with the layers and cell dimension of the reservoir one; - Modelling of specific diagenetic phenomena through transport-reaction models, in order to assess the areal distribution of diagenetic drivers in the reservoir to be used as trends; as an example, carbonate cementation though faults is one of the issues; in this step, also the structural evolution of the reservoir is a key point; - Reservoir quality prediction maps of the reservoir layers; - Use of the maps as soft drivers in the reservoir models and results comparison with other model scenarios (e.g.
Colombo, Federica (Eni S.p.A.) | Monte, Alessandro Amato del (Eni S.p.A., Eni Norge SA) | Balossino, Piero (Eni S.p.A.) | Paparozzi, Enrico (Eni S.p.A.) | Valdisturlo, Antonio (Eni S.p.A.) | Tarchiani, Cristiano (Eni S.p.A.)
A workflow applied to achieve a multi-scale characterisation of a carbonate reservoir is presented. Carbonate rocks are strongly heterogeneous due either to complexity of the primary fabric or to diagenetic over-printing. The combination of these features leads to complicated pore systems, thus a proper definition of pore types using either pore size or pore throat size distributions, is important to indirectly capture diagenetic modifications and to get a link to dynamic properties.
A new approach was developed in order to define a Rock Type classification (RRT) each time the approaches based on Winland's and Hydraulic Flow Unit methods do not give a reliable core facies characterisation when moving to the log scale. Moreover, the proposed workflow accounts for stratigraphy and seismic since RRT are linked to the elastic properties.
In the new MICP-based Rock Typing workflow, RRT are identified by describing dominant pore types using mercury injection (MICP) curves parameterisation and routine core data (RCA). Clustering and subsequent extrapolation of MICP derived RRT to RCA samples, are the first two stages to achieve a predictable classification into the log domain. Log RRT are then defined at the log scale using curves of elastic properties, like Poisson's Ratio (PR), Frame Stiffness (
This new workflow was a successful solution to define homogeneous reservoir intervals in a carbonate environment characterised by the lack of a significant relationship between depositional facies and petrophysical properties.
This paper presents a case study of integrated analysis processes, performed on a Schrader Bluff development well from the Nikaitchuq Field Alaska U.S. The reservoir consists of a few tens of feet of thick silty sand and thin siltstone layers within a structural complex setting. Wells in this field are actively steered to optimize reservoir contact. A first structural update of the reservoir model was provided by the resistivity inversion outcomes. The analysis of LWD logs allowed the identification of a suspected water-bearing layer in a structural block crossed by the well near TD. The analysis of the azimuthal density image log provided formation bed dip and azimuthal orientations along the well trajectory, enabling the recognition and classification of bedding and faulting events. Innovative commercial software was used to obtain resistivity properties through log forward modeling (Valdisturlo et al., 2013). The comparison of log responses between vertical and deviated wells thorough an electrofacies approach was helpful in recognizing the lithological characteristics of the reservoir layers, to assess the actual reservoir boundaries and to assign to the geologic model the correct log property values. The synergic combination of image log analysis, electrofacies and well log modeling resulted in a reliable stratigraphic and structural interpretation of the well. This facilitated a more accurate update of the static model and strongly improved the results of the preliminary analysis. The resistivity properties derived from the well log forward modeling gave a realistic water saturation profile confirming water presence in the structural block crossed in the last section of the drainhole. The process was completed within the scheduled time frame, allowing for the well completion plan to be amended.
Valzania, Soraya (ENI E&P) | Kfoury, Moussa (ENI E&P) | Grandis, Marco Giacomo (ENI E&P) | Valdisturlo, Antonio (ENI E&P) | Fanello, Giovanna (ENI E&P) | Guerra, Laura (ENI S.p.A) | Salah, Heikal (ENI) | Amjad, Kashif (ENI Pakistan Ltd) | Sultan, Mir Asif (ENI Pakistan Ltd)
Kadanwari field in Middle Indus Basin (Pakistan) was discovered in 1989 and brought on stream in 1995. The producing reservoirs are Cretaceous Lower Goru sands D-E-F-G. The gas production started from better quality E and F sands; after 2004 layer G started to drain western block of the field, with the first hydraulic fracture job made in Pakistan (well A). Layer G represents a complex target for petrophysical characterization; reservoir sandstones are micro-porosity rich, with variable presence of Chlorite affecting flow properties. Positive results encouraged the operator to drill & frac well B and to consider possibility to extend gas production throughout western block, including sand reservoirs of variable quality, from moderate to tight. The paper describes how reservoir study faced layer G complexity and how production data of wells A and B allowed a post fracjob evaluation integrating well-test data and frac-job interpretations into 3D dynamic model. After history match, the computed GOIP suggested an infilling program in G sand reservoir, with side-tracks of existing wells and new wells, all hydraulically
fractured. So far, one sidetrack and one new well have been drilled; results fully confirmed the complexity of local geological setting. The sidetrack revealed rock quality slightly better than expected (frac not necessary). Pilot well C targeted G-Sand in a sweet seismic anomaly in western area, a gas flare was observed during DST pre-frac. Mini-Fall Off was conducted to estimate closure pressure and effective mobility, but permeability computed from MFO was not conclusive due to important filtrate invasion. DST post hydraulic fracture job confirmed commercial gas rate production higher than 1 MMscfd with a peak of 3.5 MMscfd. The successful pilot well results open new horizon to improve reserve from tight sand of Lower Goru formation.
Capone, Graziano (ENI) | Malossi, Alfio (ENI E&P) | Mele, Maurizio (ENI AGIP SpA) | Damronsak, Chantipna (ENI Exploration & Production Div) | Valdisturlo, Antonio (ENI Exploration & Production Div) | Beretta, Enzo (ENI AGIP SpA) | Clementi, Alice (ENI E&P) | Al-shamma, Basil (ENI S.p.A.)
Reservoir characterization of laminated turbiditic sequences is often problematic due to the highly anisotropic setting, which affects the formation evaluation from conventional LWD, wireline logs and mudlog data. The reservoir, fluid content and pay petrophysical parameters are usually underestimated. Time and cost constraints can prohibit the utilization of new generation high resolution tools and to perform conventional DSTs.
An oil and gas bearing well in deep water Indonesia was accurately evaluated with a relatively low time and cost investment in formation evaluation and data acquisition. Pay, porosity and water saturation were calculated by integrating high resolution image logs with standard wireline logs. An ample dataset of reliable formation pressures and fluid samples were obtained in a thin bed environment from Wireline Formation Testing (WFT) utilizing standard and large size probes.
Mini DSTs were carried out to characterize reservoir and fluid properties. Thin beds were recognized using an imaging log in oil base mud and through a Thin Layer Analysis (TLA) approach the net sand calculation was enhanced. The TLA result was cross-checked with an electrofacies profile obtained using
standard well logs (density, neutron and gamma ray) and calibrated with the sedimentological core description from other wells. In the final net sand computation beds not corresponding with actual reservoir facies were not considered so that only the effective reservoir was included.
The result of this integrated approach resulted in an increase in the net pay evaluation in comparison with the conventional formation evaluation, and confirmed the high potential of nonconventional pay in a deep water environment. An exhaustive reservoir and fluid characterization was also achieved without coring and conventional DSTs.
1. Introduction and Operating Constrains
Eni Indonesia operates deep water blocks in the Tarakan Basin, North Kalimantan, down to 4500 ft water depth.
Deep water drilling were conducted in a remote area, more than 500 km from the nearest operating base. An appraisal well was drilled during the 2009 drilling campaign in 4000 ft water depth, to confirm the discovery of oil and gas sand reservoir and investigate the presence of possible deeper pool pay as interpreted by seismic and geological model.