Vahrenkamp, Volker (King Abdullah University of Science and Technology) | Khanna, Pankaj (King Abdullah University of Science and Technology) | Petrovic, Alexander (King Abdullah University of Science and Technology) | Ramdani, Ahmad (King Abdullah University of Science and Technology) | Putri, Indah (King Abdullah University of Science and Technology) | Sorrentino, Ranglys (King Abdullah University of Science and Technology)
The characterization and modelling of carbonate reservoirs can still be significantly improved to account for complex property and fracture network heterogeneities at scales difficult to resolve in the subsurface. The objective of this research is to develop and establish workflows for high fidelity geological modelling and characterization using modern and ancient carbonate outcrop analogues.
As a first step, we carefully selected high quality modern and ancient analogues to create comprehensive data sets on depositional heterogeneities. Advanced instrumentation and techniques were used such as 3D drone surveys, high-resolution surface geophysical surveys (50 MHz-100 MHz, and seismic), chirp sub- bottom profiler and high-resolution bathymetry mapping. These high-end techniques are paired with tried and tested standard geological techniques of measuring stratigraphic sections anchored by outcrop spectral gamma ray logs, analysis of sediment samples (texture, grain size, mineralogy, geochemistry) and fracture/fault surveys all integrated with full cores drilled in the outcrops. Using these, data models can be created for depositional and fracture heterogeneities at different scales and populated with ranges of property data like those found in actual reservoirs. The outcome will be a series of models for various carbonate reservoir settings and well location patterns with the goal of supporting drilling/exploration operations and reducing future development costs.
The project is based on two large-scale research projects of Jurassic carbonates outcropping in central KSA and a large modern carbonate platform in the Red Sea. Jurassic outcrops were analyzed using a unique dataset of measured sections including spectral gamma ray logs (300 vertical m), drone photogrammetry data (4x4 km2 overflight and several km's of vertical cliffs), seismic data (2 km), and GPR data (8 km). Data expose lateral heterogeneities, facies dimensions, and fracture networks at different scales. The modern carbonate outcrops are an ideal laboratory to investigate lateral facies heterogeneities and their relation to environmental factors influencing sediment distribution (prevailing winds versus storms, climate and nutrients). Around 800 km of hydroacoustic data, 50 sediment cores and 200 sea-floor samples were collected exposing significant and complex heterogeneities.
The outcome of these research projects significantly increases our understanding of property heterogeneity, facies distribution, fracture networks, and architecture of complex carbonate reservoirs. Resulting multi-scale modelling approaches and associated facies templates will improve the prediction of spatial heterogeneities of facies in subsurface reservoirs of similar settings. In addition, these datasets can be used as input for static analogue models and dynamic simulations to test sensitivities and determine optimum development scenarios for improving ultimate recovery.
The West Delta Deep Marine concession (WDDM) lies offshore in the Deep water of the present day Nile delta. WDDM consists of many Pliocene submarine channel complexes. The Serpent field is one of those slope marine channels and consists of two separate channels namely channel 12 and channel 13. Channel 12 is divided into three compartments by gravitational faults and channel 13 is composed of two compartments separated by stratigraphic barrier. Gas water contact (GWC) in channelized turbidities reservoir might create an intricate reservoir relationship. Gas water contact becomes complicated when the faults and the facies lateral change provide seals. Those hydrocarbon contacts depths become unpredictable without a distinct system to understand the cause of those variable contacts. Water break-through occurred earlier than expected in Serpent production wells as there was no proper modeling for reservoir facies heterogeneity and facies associated petrophysical parameters. A further compartmentalization of channel 12 arose as the sealing capacity of the gravitational faults cast a doubt over channel-12 compartmentalization and the connected gas initial in place (GIIP). The geological foreknowledge of Serpent field, the production issues and the dire need for further development plans in Serpent field were the motives to initiate this study. Integrated study was designed to answer the unsolved challenges of characterizing the reservoir heterogeneity and faults' sealing capacity. 3-D (three dimensional) high quality seismic data and different seismic attributes were integrated with different well data to build a robust 3-D static model. Static model was the way to elaborate the facies accurate distribution and the different petrophysical parameters in Serpent reservoir. In addition, the 3-D static model was used in the prediction of the faults' sealing capacity through the fault rock facies, fault rock petrophysical properties and transmissibility. In a nutshell, the resultant static model answered the field's issues regarding the early water production, facies heterogeneity and Successfully isolate the different reservoir compartments then run into prediction to assess the potential of the existing well-stock and any future development plans in Serpent field.
Increased demand for gas in the recent years has motivated Exploration companies to revisit erstwhile overlooked Miocene Biogenic gas potentials, onshore Abu Dhabi. This paper detail how advanced geophysics techniques including rock physics forward modeling and inversion has been integrated to understand the distribution of potential gas bearing zones in this complex unconventional setting where inter-well information is limited. The results integrated with understandings from other disciplines support drilling and field appraisal strategy in the area.
The Miocene Formation of interest consists of an Upper, Middle and Lower unit, with varying levels of complexities and hydrocarbon presence identified from drilled wells. We show how we integrated all available data including logs, core, fluids, cuttings, mud-gas, petrophysical and seismic information to constrain the seismic forward model and invert the seismic data to define potential for gas presence in the area. Lithologic boundaries were defined from cuttings and geologic correlations. Half-space rock properties analyses and well ties provided understanding of the seismic responses, and the geologic picks mapped accordingly. Gassmann fluid substitution were carried out using conditioned Vp, Vs and density logs to understand the sensitivity of the lithologies to different pore fluid fill including brine and different gas proportions. AVO forward modeling was also carried out to understand if gas ‘sweet spots’ may be visible from analyses of amplitudes. Rock physics plots were analysed including AI, SI, GI, PI and Lame's parameters to establish relationship to reservoir properties, and optimum discriminators of fluid, porosity and TOC were accordingly determined. The low frequency model was developed from logs, and prestack 2D seismic data up to 40° were inverted for elastic impedances. Bayesian rock type classification scheme was deployed to extract potential gas prolific areas.
Seismic rock properties analyses provided invaluable insight to the reservoir characterisation strategy for the Biogenic gas formation. The analyses showed that delineating gas presence is challenging using conventional amplitude or AVO analyses techniques. Potential for fluid optimization exists from analyses of poisson's impedance (PI) as well as extended elastic impedance at the fluid projection with reasonable certainty. Pre-stack simultaneous inversion of the seismic lines was carried out, followed by Bayesian rock type classification to identify regions of increased gas potential in areas of seismic coverage
This paper represents for the first time integrated seismic rock properties and inversion techniques are applied to delineate an unconventional Biogenic gas reservoir. The results hold potential benefit for well placement and input to distribution of reservoir properties in the geologic model. The method will be extended to analyzing the gas potential from the currently acquired mega 3D seismic over Abu Dhabi.
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.
Complex hydrocarbon distributions where reservoirs are filled by oil and gas phases with different densities and genetic types interfingering within a basin are a common phenomenon in Southeast Asia and are often attributed to vertical migration. Attempts to understanding the controlling factors of vertical hydrocarbon migration by modeling the hydrocarbon charging and entrapment history from two Cenozoic basins in Southeast Asia—West Java and the Madura Platform—are discussed.
A modified invasion percolation algorithm was used to simulate the secondary migration models, which follows the principle that migration occurs in a state of capillary equilibrium in a flow regime dominated by buoyancy and capillary forces. Three-dimensional (3D) seismic data were used as the base grid for migration simulation to capture the effect of both structure and facies variations on fluid flow.
Two models, one from the West Java Basin (fault-bounded structure) and the East Java Basin (nonfault-bounded structure), are presented. For both cases, interfingering between oil and gas occurred, with most oils trapped within the lower formations, a mixture of oil and gas dominates the middle formations, and mostly gas in the upper formation. These vertical arrangements are possible because of the relatively weak formational seals within the basin. For vertically distributed reservoirs, oil is often trapped within the lower interval, and gas is trapped at the upper interval. For a basin dominated by a vertical migration regime, the potential risk for hydrocarbon lateral travel far away from the kitchen is high, thus increasing the potential risk of prospectivity away from the kitchen. Understanding factors that help control vertical migration also help geologists better understand hydrocarbon distributions within the basins.
Case studies during which modeling helped determine the factors that influenced vertical hydrocarbon migration and the resulting potential phase distribution prospectivity risks in the studied basins are discussed.
Thin turbidity siliciclastic reservoir is a challenging deep-water environment for modeling. In a deep off-shore field in West Africa, sedimentological characterization of these reservoir suggests typical turbiditic sandstones: Arenites with medium granulometry and normal gradation over imposed by plane-parallel sand laminations intercalated by shaly levels (late stage turbidity sandstone beds - characterization by
These sands are defined in the reservoir model by curves of petrophysical properties, log facies, characterization of thin bedded intervals and a volume of seismic inversion.
Tuning analysis suggest the potential seismic resolution is 16 meters. Seismic inversion was processed to generate a higher resolution driver for modelling.
Formation evaluation uses high-resolution logs within "Thin Layer Analysis and Characterization" (e-tlac™) method (
High-resolution logs were acquired only in three wells over twelve drilled in the field. For this reason, a re-calibration of all conventional CPIs including the "e-tlac" output results was necessary to better control the reservoir property distribution all over the grid.
This methodology increased capability estimating pay volume close to real value avoiding underestimation of Net Sand and Water Saturation overestimation.
The solution to model thin turbiditic sands within the static 3D model is integrating all the above data inputs (stratigraphical environment, seismic inversion volume and "e-tlac" output). Reservoir cores was the input for the sedimentological study; the seismic inversion volume was background for reservoir facies distribution and "e-tlac™" formation evaluation output to assign unbiased reservoir properties to sand and thin layer facies at the well position.
As lesson learned, the acquisition of triaxial induction, high-resolution dielectric or image is the key to better characterize the inter-bedded thin levels that are present in similar deep-water environment.
Moharana, Abhishek (Schlumberger) | Mahapatra, Mahabir Prasad (Schlumberger) | Chakraborty, Subrata Kumar (Schlumberger) | Biswal, Debakanta (Adani Welspun Exploration Limited) | Havelia, Khushboo (Schlumberger)
Petroleum Geologists have always been a group who looked at rocks, developed and described depositional concepts, mapping structures to discover and develop hydrocarbons for profit. With the advent of new technologies and computing power, geology started to become a lot more quantitative. The first wave of this new revolution was the introduction of geostatistics and the discipline of geomodelling, dealing with quantitative statistics like variograms, histograms, stochastic models which could be used to put a number and range on the geological uncertainty. However, geostatistics which was originally developed in the mining industry in the 1950's deals more with regularly sampled data, describing their spatial variability and directionality. In majority of development fields, with many wells sampling the reservoir, geostatistics helps us to create a feasible proxy for the subsurface reservoirs, when it is backed by a strong conceptual geological foundation. However, as the number of wells decreases, the data for geostatistical analysis reduces and a geomodeller must rely strongly on the conceptual geological knowledge, to build a predictive geological model rather than the noisy picture which over-reliance on blind geostatistics can provide. Until recently, there was no way of quantifying or visualizing depositional concepts in 3D for a geologist save for few block diagrams and average sand distribution maps. However, these were mostly manual, deterministic with a long turnaround time for any alternate concepts.
A relatively recent and still underused addition to the geologist's set of quantitative tools has been geologic process modeling (or GPM, also called stratigraphic forward modeling). This technique aims to model the processes of erosion, transport and deposition of clastic sediments, as well as carbonate growth and redistribution on the basis of quantitative deterministic physical principles (
In the currents study a 3D geological model for the B-9 field, based on the Geological Process Modeling (GPM) has been attempted Owing to the thin pays in deltaic sands, understanding reservoir continuity from seismic data was not possible. With only 4 wells available in the field, traditional geostatistics based facies models were inadequate in explaining the reservoir distribution. Thus, a combination of Stratigraphic Forward Modeling with Multi Point Statistics is used to accurately capture sub-surface facies heterogeneity.
In carbonates, the geological facies is a key driver for populating reservoir models with petrophysical properties. Conventionnal core analysis mainly contributes to establish relationships between facies, petrophysics and geophysics. However, populating gridblocks reservoir models with petrophysics requires parsimonious facies classifications and effective relationships at larger scales that field studies rarely investigate. Studying outcrop analogues helps filling the gap between lab measurements and effective upscaled properties of models, and considerably improves the modelling workflows.
The ALBION R&D project developed an innovative framework for multi-physics and multi-scales characterization of Barremian-Aptian carbonates from south-eastern France. These outcropping rudist-rich limestones constitute an analogue of Middle-East reservoirs. Petrophysical and geophysical properties were measured on plugs from cores and outcrops but also at larger scales thanks to original experiments on cores, in and between boreholes. Indeed the analogue includes several experimental areas, where hydraulic tests in sealed wells sections and tomographies between very close boreholes allowed investigating petrophysical and geophysical rock properties at intermediate decimetric to decametric scales. Thanks to the resulting database, this paper aims quantifying the variability of multi-physics data (e.g. porosity, permeability, and P-wave velocity) at different scales in regards of an updated and unified facies classification. The latter is only based on sedimentary origin and fabrics. Other available properties affecting petrophysics are used to cluster facies associations in sub-classes.
Consequently the facies classification does not allow discriminating the distributions of porosity, permeability, nor p-wave velocity. For the rudist facies, that is the most sampled, texture subclasses do not help this work. Reversely, the place of sampling, that is likely a proxy of diagenesis and age, cluster the petrophysical distributions. The results remind us that a proper facies definition should consider both sedimentary origin, fabrics, texture, diagenesis and tectonics. They also point out the relative importance of each characteristics in regards of the scale of interest and the difficulty to infer upscaled relationships between rock properties from CCAL because the representative elementary volume of carbonates is usually higher than the plug and even the core volumes.
Al-Hammadi, Mariam Khalil (ADNOC OFFSHORE) | Sinha, Amit Kumar (ADNOC OFFSHORE) | Zakaria, Hasan Mohammed (ADNOC OFFSHORE) | Agrawal, Pawan (ADNOC OFFSHORE) | Al-Badi, Bader Saif (ADNOC OFFSHORE) | Al-Hassani, Sultan Dahi (ADNOC OFFSHORE) | Ahmed, Shafiq (ADNOC OFFSHORE) | Mohammed Khan, Owais (ADNOC OFFSHORE)
Field presented here is giant heterogeneous carbonate field consist of multi-stacked reservoirs, located in offshore Abu Dhabi. This paper presents development plan for one of reservoir. It consists of a very large rich gas cap with oil rim. Current development plan is oil production from oil rim with peripheral water injection with no gas injection and production. Significant amount of data (Core, Seismic, Logs, DST, production test & PTA) during the early production period have been collected. All the data have been integrated to prepare robust Co-development of oil-rim and gas cap to maximize oil and condensate value from the reservoir.
Reservoir consists of three main porous units: Upper, Middle and Lower Units inter-bedded with dense intervals. Generally the best porosity development is seen in the norther part of the field. Sedimentology study was mainly focused in the upper section of the reservoir. Five facies associations were made based on a low inclination ramp depositional model and diagenetic impact honoring the paragenetic sequence. Facies controlled diagenesis was noticed where abundance of echinoderms controlled the different degree of cementation degrading the reservoir quality. Identifying these dominant echinoderm facies zones allows us better well placement by avoiding them. The output of this study was four facies maps with five facies association distribution representing the four cycles seen in the upper part of the reservoir which is the best reservoir section. These facies maps were incorporated for property distribution in the static model.
The reservoir model is constructed using latest acquired seismic and more than 100s of well control for the top of the Reservoir, used as reference structure. Proportional layering was used for different reservoir layers which have been mapped using Isochore. The facies association was distributed using trend map and Vertical proportion curve observed on the Well. Reservoir properties like Porosity and Permeability were distributed using constrained of facies distribution. A newly drilled well also used as for blind test showing the predictability of the model. Dynamic data such PTA and time-lapse MDT has been integrated in the updated model to guide areal and vertical connectivity. Good history matching has been obtained with minimal changes in the static model.
With the updated model different sensitivities of gas cap and oil rim development has carried out in terms of co-development timing, lean gas recycling volume, and inner ring water injection in order to maximize oil and condensate value from the reservoir and avoid oil migration in the gas cap.
In carbonates, predicting permeability values for gridded reservoir models is very challenging as it involves both the difficult characterization of a very heterogeneous medium, the uncertain extrapolation far from well data, and the up-scaling concern. The quantification of effective permeability for model gridblocks using small scale data from plug measurements or log interpretation is a recurrent concern since the change of support for permeability has proved to be definitively non linear. When a well test interpretation is available, it gives the evolution of the permeability in the vicinity of the wells for a volume much larger than the volumes characterized by cores and logs. In that case, the consistency has to be found between the transient pressure analysis-derived large scale equivalent permeability and the small scale permeability issued from conventional core analysis or log interpretation.
It is known that the upscaling can be expressed as some power average of the permeability distribution, and that an analytical formula relates the horizontal permeability in the volume investigated by the well test and the original small-scale permeability distribution in this volume. However, the relation between the upscaling law and the permeability structures is usually documented for a few number of structures, leading to recurrent problems when large scale permeability has to be extrapolated outside the volume explored by the well test.
A new formulation of the power averaging coefficient has been proposed, which relates the power averaging coefficient to the geostatistical description of the permeability structures, the direction of the flow, and the volume for which the equivalent permeability is computed. The new methodology has been applied to the Buissonniere field laboratory, a site from the ALBION R&D Project. Thanks to a characterization at an unusual scale, the integration of geological, petrophysical, geophysical and pressure transient data has successfully validated the use of this new formulation.