Ferreira, Joana (University of Lisbon, Faculty of Sciences, Department of Geology) | Azerêdo, Ana C. (University of Lisbon, Faculty of Sciences, Department of Geology and Instituto Dom Luiz) | Bizarro, Paulo (Partex Oil & Gas) | Ribeiro, Maria Teresa (Partex Oil & Gas) | Sousa, Ana (Partex Oil & Gas)
Characterizing highly heterogeneous carbonate reservoirs requires the integration and detailed analysis of petrophysics, facies, diagenesis, geometry, depositional environments and lateral and vertical variability. This is often challenging to conceptual models at oil-field scale, as this thorough analysis is hard to fully reproduce at reservoir-scale models. In order to improve skills and interpretations on both approaches, we addressed a case study from a Middle Jurassic outcrop of Portugal as an analogue for a carbonate reservoir.
The outcrop exhibits three barrier shoreface lithofacies: L1 - oolitic and bio-intraclastic grainstones (divided into: L1a- with planar stratification or unstructured; L1b - with diverse cross-stratification styles); L2 - coarser grained grainstones/rudstones; and L3- coral/algal biostromes. Outcrop analysis was combined with petrographic/diagenetic studies of rock samples. Regarding petrophysical properties, three methods were used to determine the porosity: thin-section impregnation with blue-dyed epoxy resin, rock-slab water saturation and, for a few samples, plug measurements in a Helium gas expansion porosimeter. The plugs were also used to acquire permeability values using a digital gas permeameter.
The results show that the outcrop is a tight reservoir, since most levels have low porosity (~3.5% average) and permeability (mostly <0.1md), though higher values (φ~10-15% and K~160md) occur locally. Most levels are classified as hybrid 1 or diagenetic reservoirs, according to
Normal industry workflows often do not fully consider geological data and conceptual models, and instead rely heavily on geostatistical propagation of well data. The results obtained indicate that there is an improvement in reservoir understanding with an integrated reservoir characterization and modelling process that accounts for actual depositional and diagenetic trends, as well as the distribution of the sedimentary bodies.
Project partners want field operators to achieve production targets and deliver projects in the defined timeframe within budgetary limits. However, operators are frequently unable to achieve the goals projected at the launch stage of the project. This compromises the initial project economic value and originates conflicts between partners’ anticipations and the actual project outcomes. Such inconsistency is frequently due to wrongful and/or insufficient perception on risk management policies employed by both parties: operators often compromise the application of a holistic risk management framework, by concentrating their efforts around particular project segments, such as HSE, fluids production and/or oil price; partners, being heavily dependent on operator efficiency and competence, have limited tools to control project performance and usually rely or accept selected risk management methods.
This paper presents a general risk management approach for the oil and gas industry based on the knowledge gained in petroleum projects. The proposed methodology offers a coherent approach, which can aid in improving the risk management strategy of both operators and partners. The challenge is in developing a simplistic, but yet effective and dependable method, which can be utilized by consortiums in any oil and gas ventures.
The result of this paper is a Risk Management Roadmap (RMR) that provides all stakeholders with concrete tools to assess and categorize project risks, quantifying their potential economic impact and hold major threats within acceptable levels.
This paper attempts to provide relevant implications for both parties: operators enable an effective communication with partners facilitating a clear and common language for mutual cooperation and progression towards the project targets; partners benefit from taking better informed decisions, protecting shareholders’ interests, having stronger control and influence over the desired project outcome.
Many petroleum projects are being executed through the partnerships where operator “holds the rights to exploration and development of petroleum resources” with the objective to deliver the promised value of the project. Partners “make the investments needed to meet projected demand for oil” being focused on protection of shareholders’ interests and successful performance of their asset. Despite this, many projects fail to deliver on costs, schedule, operability and safety commitments resulting in disappointed financial outcomes and deterioration of the relationships between stakeholders. In this instance, effective management of risks becomes critical for both parties.
In oil and gas partnerships, the level of the project control tends to vary according to the role of the participants: operator has a direct control and responsibility over the project execution, being also accountable for the development of an effective Risk Management (RM) system; partners tend to provide technical and financial support relying on the effectiveness of the RM methodology chosen by the operator.
Reservoir characterization and modelling of highly heterogeneous carbonate reservoirs encompasses the interplay between petrophysical properties, facies, diagenesis, and their relationship with depositional environments. This case study describe a strongly dolomitized carbonate reservoir of Valanginian age onshore Kazakhstan, Central Asia. A reservoir model was built by using an integrated workflow with all the available data, namely seismic, cores, thin sections, logs and MICP. In order to build a robust subsurface model and reduce uncertainties, reservoir rock types (RRTs) were defined and modelled honouring depositional trends and diagenetic attributes.
Due to the complexity of the reservoir, the Winland R35 method, together with Lorenz plots and petrophysical groups, was used to derive the RRTs and to assign a porosity-permeability relationship for each RRT. The uncertainty in the reservoir property models was evaluated with different RRT connectivity scenarios, driven by depositional and diagenetic concepts.
With the integration of diagenetic trends in the model, it was possible to capture the heterogeneity of the reservoir and better understand the porosity and permeability distributions. This has led to development plan optimization through the definition of sweet spot areas and an improved STOIIP calculation.
The results indicate that a substantial improvement in reservoir understanding can be achieved with an integrated reservoir characterization and modelling process that accounts for depositional and diagenetic trends, especially in reducing subsurface uncertainty. Furthermore, it was possible to recognize spatial trends and capture the relationship between petrophysical properties, pore architecture and sweep efficiency. It is expected that the ultimate recovery will also improve.
The case study field is located onshore Kazakhstan, and comprises several oil bearing units. The principal reservoir corresponds to Aptian deltaic-marine sands, whereas this study addresses a secondary reservoir, which is the Valanginian carbonate. The producing structure is an E-W oriented anticline with a western downdip, where some faults are present.
The Carbonate reservoir was discovered as an upside in the mid-2000’s while drilling an exploration well. Encouraging flow tests from a 6 m interval have led to the kick-off of a detailed reservoir modelling exercise, in order to support a development plan. After that, a first pass static model was done with just a few wells. More recently, several appraisal wells were drilled to delineate the extent of the Carbonate reservoir.
The Valanginian Carbonate comprises fine grained limestone, dolomite and marl. This total interval is some 370-400 m thick (Figure 1). The oil bearing unit itself occurs in the uppermost part of the interval, and is mainly composed of skeletal dolopackstone, dolowackestone/dolopackstone, doloboundstones, with some intervals of dolomudstones. This oil bearing unit presents layer cake geometry, and is sealed by anhydrite.
This paper describes the work undertaken to build a 3D static model of a Lower Cretaceous Carbonate Reservoir located in Kazakhstan called X-Field. This reservoir has been pervasively dolomitized, and presents several challenges for development optimization. This model will be used to support further appraisal and development activities, in order to tackle key uncertainties, such as reservoir quality distribution.
All of the available data were quality controlled, analyzed and interpreted (including data from logs and cores), to produce porosity, permeability and RRT (reservoir rock type) models. These are believed to be representative of the reservoir's behavior and connectivity.
In order to identify the main flow zones and understand the reservoir's complexity, Reservoir Rock Typing (RRT) was performed on two cored wells by analyzing CCAL and SCAL data, including thin sections, MICP measurements, porosity and permeability. A comprehensive RRT methodology using Winland R35 method and poro-perm plot was followed, which resulted in defining five rock types. The outcome from the RRT study was confirmed by poro-perm plot, which showed the presence of five flow units.
The 3D model was built by using corner point grids (CPG), and contains a total of 2,380,050 cells. Several models of porosity and RRT were generated, representing "low??, "mid??, and "high?? case scenarios of reservoir quality distribution. Finally, permeability models were created for each scenario, conditioned to their respective Winland R35 porosity-permeability relationships per RRT.
Comparison between the different porosity (F), permeability (k), and RRT models and scenarios, will allow a better management of the reservoir uncertainties during the appraisal and development stages for this reservoir.
Carbonate reservoirs are commonly heterogeneous and their reservoir quality results from complex interactions between depositional facies and diagenetic processes. The Diagenetic Diagram is a powerful tool that helps in the characterization of the diagenetic processes that have affected the reservoir. From this knowledge, it is possible to significantly improve the understanding of the reservoir's pore system and permeability distributions, which are key factors for development optimization and production sustainability.
A multi-scale and multi-method study (petrography, blue-dye impregnation, selective staining and porosity determination) of Middle Jurassic carbonates from the Lusitanian Basin (Portugal) has been undertaken, to find the best systematic approach to these reservoirs. It has involved thorough diagenetic characterization of each lithotype (lithofacies, texture, porosity, qualitative permeability assessment and diagenetic evolution). The study area was selected based on its excellent and varied exposures of carbonate facies and availability of core.
Methodological and terminological challenges were faced during the study, especially dealing with data coming from several scales (macro, meso, and micro). In order to overcome these challenges, a diagenetic diagram was developed and applied to the selected rocks. It is a tool that allows the integration of data coming from outcrops, hand samples, cores, cuttings, thin sections, and laboratory experiments.
This is carried out in a dynamic, guided, systematic, and rigorous way, enabling the evaluation of the relationship between facies, diagenetic evolution and pore systems. The latter are characterized regarding size, geometry, distribution, and connectivity. This enables the identification and characterization of permeability heterogeneities in the rocks. It was concluded that the main porosity class (i.e. secondary) was created by diagenetic processes.
The proposed method has strong application potential for: detailed characterization and understanding of porosity and permeability in carbonate reservoirs, from a diagenetic evolution and fluid flow perspective (e.g. SCAL and pore system description); definition of diagenetic trends for modeling petrophysical properties and rock types. In this regard, the method is being applied to a Valanginian carbonate reservoir in Kazakhstan, and some preliminary results are presented in this paper. Refining this technique may be helpful for similar carbonate studies, enhancing the results of typical diagenetic studies by improving the characterization of reservoir properties at various scales, thus contributing to a more sustainable exploitation of hydrocarbon reservoirs.
Lawrence, David A. (ADCO) | Al Ali, Malalla (Abu Dhabi Co. Onshore Oil Opn.) | Vahrenkamp, Volker C. (Abu Dhabi Co. Onshore Oil Opn.) | Al Shekaili, Fatema (Abu Dhabi Co. Onshore Oil Opn.) | Yin, Yahui (ADCO Producing Co. Inc.) | El Wazir, Zinhom Ali (Abu Dhabi Co. Onshore Oil Opn.) | Ribeiro, Maria Teresa (Partex Oil and Gas) | Mueller, Klaus W. (Abu Dhabi Co. Onshore Oil Opn) | Al-Madani, Noura Mohammed (ADCO Producing Co. Inc.)
A super-giant carbonate field in Abu Dhabi has most of its remaining reserves in carbonate build-up and prograding basinmargin deposits of Lower Cretaceous age (Shuaiba Formation). To guide further field production, a sequence stratigraphic framework was developed based on integration of core, log and seismic data. This framework is the cornerstone for building a new reservoir model and provides the key for a better understanding of facies and flow unit continuity guiding present and future field production and performance.
Approximately 730 wells, wireline logs and the latest core descriptions were integrated for this study. Another key element was the incorporation of 3D seismic data coupled with several iterations between well log and seismic picking. Detailed seismic interpretation led to the delineation of 3rd and 4th order sequences. The picking of higher order sequences was based on well data guided by the seismic surfaces. This study provides an excellent example of extracting maximum information from seismic and the full integration of geoscience and production data to provide a new 3D framework.
The sequence framework uses a consistent nomenclature based on the Arabian Plate Standard Sequence framework for the Aptian (van Buchem et. al., 2010). The Shuaiba is subdivided into six 3rd order sequences (Apt 1, 2, 3,4a, 4b, and 5) which, based on stacking patterns, record a complete 2nd order cycle of Transgressive, Highstand, and Late Highstand systems tracts (Apt 1-4b). The Bab Member (Apt 5) and Nahr Umr Shale form the Lowstand to Transgressive systems tracts of the next Super-sequence.
The third order Apt 1 sequence and the Apt 2 TST form the 2nd order transgressive systems tract, characterized by backstepping and creation of differential relief between the Shuaiba shelf and Bab intra-shelf basin. These sequences are dominated by Orbitolina and algal/microbial Lithocodium/Bacinella fossil associations.
The Apt 2 HST and Apt 3 Sequence form the 2nd order early highstand systems tract during which the platform area aggraded and the topographic split into platform, slope and basin became most pronounced. Sediments are extremely heterogeneous and varying properties introduce significant problems in understanding fluid flow. During the regressive part of the Apt 3 sequence accommodation space was limited and deposition switched to progradation at the platform margin. The platform top is characterized by thin cycles of rudist floatstones/rudstones separated by thin cemented flooding and exposure horizons, whilst
the platform margin received large quantities of rudstones, grain and packstones organized in clinoform sets. Clinoforms are separated by thin stylolitic cemented layers, which are transparent on seismic.
The Second Order late highstand systems tract is composed of 3rd order cycles Apt 4a and Apt 4b. These are detached from the main buildup, which probably stayed largely exposed, and form strongly prograding slope margin wedges composed of alternating dense mudstones (TST) and grainstone/packstone sequences with coarse grained top-sets which formed during highstand phases. Lowstand deposits of the Apt 5 cycle (Bab Member) are dominated by fine-grained siliciclastics capped by thin oolitic carbonate facies which are isolated from the main part of the field and are not hydrocarbon charged.
Gomes, Jorge Salgado (Abu Dhabi Co. Onshore Oil Opn.) | Ribeiro, Maria Teresa (Abu Dhabi Co. Onshore Oil Opn.) | Strohmenger, Christian J. (ExxonMobil Exploration Co.) | Naghban, Shahin (Abu Dhabi Co. Onshore Oil Opn.) | Kalam, Mohammed Zubair
Reservoir rock typing is a process by which geological facies are characterized by their dynamic behavior. The dynamic behavior of the facies is assessed by studying the rock texture, the diagenetic processes which overprinted the initial fabric, and the interaction between the rock itself and the fluids. Porosity, permeability and pore size distributions characterize the rock texture while capillary pressure, relative permeability and wettability describe the rock-fluid interaction.
Reservoir rock typing is a synergetic process between geology and petrophysics/SCAL. It is therefore a process by which various petrophysical parameters and dynamic measurements obtained from SCAL are integrated in a consistent manner with geological facies (lithofacies) to estimate their flow (dynamic) behavior.
The relationships between lithofacies and reservoir rock types (RRTs) is complex because of the inter-play between facies, diagenetic processes and the rock-fluid interaction (wettability changes) in the reservoir. Similar lithofacies, deposited under the same depositional environments, may exhibit different petrophysical properties due to diagenesis. Therefore, lithofacies deposited under similar geological conditions may experience different diagenetic processes resulting in different petrophysical groups with distinct porosity-permeability relationship, capillary pressure profile and water saturation (Sw) for a given height above the Free Water Level (FWL). On the contrary, lithofacies deposited in different depositional environments, might exhibit similar petrophysical properties and dynamic behavior.
The authors emphasize on the need to have a good understanding of the original facies, depositional environments, subsequent diagenetic processes and rock-fluid interaction (via SCAL) to be able to unravel the relationships between lithofacies, petrophysical groups and rock types.
A workflow for carbonate rock typing addressing some of the industry pitfalls and the differences between lithofacies, petrophysical groups and rock types are presented in this paper.
Introduction - Nomenclature
Before proceeding into the rock type description and its link with geology and SCAL, it is important to provide a few basic definitions of the common technical terminologies found in the literature such as lithofacies, facies associations, petrophysical groups, rock types and flow units. In this paper we define lithofacies or lithofacies types as a depositional facies, or lithotype, based on sedimentary texture (Dunham 1962; Embry and Klovan 1971), grain types (skeletal grains, peloids, ooids, etc.), and, optionally, sedimentary structures (cross-bedding, bioturbation, lamination, etc.). Typical lithofacies types are skeletal wackestone, skeletal-peloid packstone or cross-bedded ooid grainstone. Facies associations are groups or bins of lithofacies from the same depositional environment/facies tracks with common f-k relationships/trends. Petrophysical groups are units of rocks (can consist of multiple lithofacies) with similar petrophysical correlations and common porosity and permeability bins in the f, k domain.
Petrophysical groups can be characterized by conventional core analysis and Mercury Injection Capillar Pressure (MICP) data. Flow units are petrophysical groups with spatial continuity at the Field scale. They define the hydraulic units or flow zones (layering) of the reservoir, which should be preserved during upscaling. So, flow units, hydraulic units and speed zones are all expressions with similar meaning. Rock types are units of rock deposited under similar geological conditions (not a must), which experienced similar diagenetic processes resulting in a unique pore network and wettability, which is translated into a unique f-k relationship, capillary pressure profile and relative permeability dataset for a given height above the FWL. Rock types are therefore characterized using SCAL data. MICP and conventional core analysis are not enough to characterize rock types.
Arslan, Izzet (Abu Dhabi Co. Onshore Oil Opn.) | Ribeiro, Maria Teresa (Abu Dhabi Co. Onshore Oil Opn.) | Al Neaimi, Mohamed Ahmed Abdullah (Abu Dhabi Co. Onshore Oil Opn.) | Hendrawan, Irfan (Abu Dhabi Co. Onshore Oil Opn.)
A new breakthrough in reservoir modeling is using Training Images (TI) with Multiple Point Statistics (MPS). A TI is a structural image of a reservoir layer or stratigraphic time interval, which represents all the relevant events (e.g. facies) at a time independently from a real location. Therefore, the TI's capsulate much broad geological sense with conceptual patterns or multiple joint relations beyond the traditional geostatistics where it may merely offer two-point correlations (e.g. variograms) with sparse well data.
Each time sequence presents a transgression within Arabian plate along hundreds of km's distance length one would not see the whole sequence of a platform (e.g. lagoon, ramp and shoal deposits) through a relatively small reservoir area (30km x 30 km). This brings a common challenge in facies modeling of carbonate reservoirs regarding lateral changes in deposition settings that are rarely crossed along the small scale reservoir sequences although a diversity of facies types can be observed vertically.
The Arabian Gulf plate reservoir of Lower Thamama around Abu Dhabi was studied to understand how a relatively limited reservoir area was deposited through the help of TI's. A rock-type study based on core and log data was compiled, and 23 facies types varying vertically were identified. TI's were drawn for each time interval between high resolution sequence stratigraphy (HRSS) picks. It was not eligible to drive properties through seismic attributes since the seismic attributes were weak for tuning the facies heterogeneity. The analogs, representing the depositional strata sketch were mapped with outcrop data, core descriptions and solid geological knowledge of the reservoir. Given these conceptual images conditionally, all possible scenarios of the deposition were simulated with MPS algorithms. Uncertainty analysis was also performed to infer the variability of the different TI's.
Al-Hajeri, Salma Khalfan (Abu Dhabi Co. Onshore Oil Opn.) | Ayoub, Mohammed Ramadan (Abu Dhabi Co. Onshore Oil Opn.) | Al Shehhi, Abeer Saif (Abu Dhabi Co. Onshore Oil Opn.) | Negahban, Shahin (BP) | Ribeiro, Maria Teresa (Abu Dhabi Co. Onshore Oil Opn.) | Bahamaish, Jamal Nasir (Abu Dhabi Co. Onshore Oil Opn.)
Tight carbonate reservoirs, although less well understood and believed to require higher development costs and risks than conventional reservoirs, have become an important resource. Historically, tight reservoirs have been unpopular and unfavorable with geologists and reservoir engineers mainly due to difficulty associated with their development with no commercial productive value. Recently, with the increase in demand for oil and continuous development of new technologies, the time is right to carefully examine and develop such reservoirs.
This paper discusses the development of one of the tightest carbonate reservoirs offshore Abu Dhabi, UAE. Initially, this reservoir was not planned to be developed based on the appraisal data collected. The average reservoir permeability is around 1 mD with a productivity index of 0.4 bod/psi. However, an intensive work was performed to evaluate the reservoir potential as being commercially attractive. Such process included gathering of additional data during the development of a major reservoir located below and the review of the core and test permeability data across the reservoir.
Several model scenarios were created both on static and dynamic sides as well as an evaluation of the uncertainties and associated development risks.
Effectiveness of the study took place when drilling horizontal wells across the most permeable intervals resulted in a production five times higher than expected. This resulted in a decision to embark on the field development and additional production data gathering for development optimization.