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Collaborating Authors
Naturally Fractured Carbonate Reservoir Characterization: A Case Study of a Mature High-Pour Point Oil Field in Hungary
Ali Akbar, Muhammad Nur (MOL Hungary) | Nemes, István (MOL Hungary) | Bihari, Zsolt (MOL Hungary) | Soltész, Helga (MOL Hungary) | Bárány, Ágnes (MOL Hungary) | Tóth, László (MOL Hungary) | Borka, Szabolcs (MOL Hungary) | Ferincz, György (MOL Hungary)
Abstract An integrated technical study was conducted for a field development project in West-Hungary. This study offers a better solution for estimating petrophysical properties and fracture facies vertically along the well and laterally for 3D static and dynamic models of naturally fractured reservoirs in carbonate rocks. More than 30 wells with 40 years of production history were used in order to build reliable static and dynamic models. The fracture class/facies plays essential role in spatial distribution of petrophysical properties during 3D reservoir modeling. It was defined by integrating the conventional logs, image logs, drilling parameters, and production or well test data. Three fracture facies are defined as macro-fracture (including permeable sub-seismic fault), micro-fracture, and hostrock. Subsequently the fracture-class's spatial distribution is guided by seismic attributes of faultlikelihood combined with geological concept of fault and damage zone. As a result, the established fracture classes along the wells are validated by static and dynamic subsurface data. Spherical self-organizing map (SOM) was also implemented for predicting the fracture location in wells having limited subsurface data. Moreover, fracture lateral distribution follows the distribution of the fault zone of fault core, high-damage zone, low-damage zone, and host-rock. The higher the fault displacement the wider the damage zone and fault core formed. Macrofractures and micro-fractures frequently appear around fault core and high damage zone. While only microfractures are dominantly present in the low damaged zones. In contrast, the unfractured class is dominantly distributed in host rock area. Also, the lithologis considered in distributing the fracture class because the rock mechanic properties and number of fractures are strongly controlled by rock compositions. Once the fracture class is distributed, porosity, permeability, and water saturation are modelled in the 3D geocellular model. Finally, this fracture class also plays a role as a rock typing for reservoir simulation. The saturation height model is built using the fracture class distribution resulting the initialization, history matching process, and production forecast from 20 wells are showing excellent quality. As a novelty, this study offers a better understanding of fracture distribution and accelerates the history matching process with a more confident result of production forecast. In the absence of advanced technologies like image logs and production logging (PLT) measurements, this study still effectively assists us to recognize the fracture presence and its quality in both well-depth interval and 3D spatial space, and successfully guided us in proposing a new infill drilling with strong confidence and delivering on the high-end of expected results.
- Europe > Hungary (1.00)
- Asia > Middle East (1.00)
- North America > United States > Texas (0.46)
- Geology > Structural Geology > Fault (1.00)
- Geology > Rock Type > Sedimentary Rock > Carbonate Rock (0.49)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.46)
- (2 more...)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Borehole Seismic Surveying (0.94)
- Geophysics > Seismic Surveying > Seismic Interpretation (0.69)
- North America > United States > Texas > Permian Basin > Wolfcamp Formation (0.99)
- North America > United States > Texas > Permian Basin > Midland Basin (0.99)
- North America > United States > New Mexico > Permian Basin > Wolfcamp Formation (0.99)
- (9 more...)
Abstract Characterizing the naturally fractured reservoir in a mature field is always a challenging task due to minimal subsurface data availability and the technology was not as advanced as nowadays. Therefore, this paper is proposed to provide an alternative solution to identify the presence of the fractures, classify them into the fractured quality related flowability, and distribute them vertically within the well interval and propose a lateral distribution method for reservoir modeling. This research was conducted based on a case study of basement fractured carbonate reservoir in Hungary. I used more than twenty development wells which mainly drilled during 1980-2000's. The fractures presence is simply identified by using gamma-ray and density logs. The relative movement of density log to the defined fractured baselines was directed to classify the fracture quality within three groups of macro-fracture, micro-fracture, and host-rock. These groups were validated by core data and the acoustic image log from the newest drilled wells. Furthermore, I implemented the self-organizing map (SOM) for distributing the fracture group to other wells which having limited subsurface data. Since the fracture classes were distributed along the well depth interval, then the well test (DST) results and production flow test data validated the flowability of them. As a result, the main flow contribution intervals of the fracture can be well-recognized. The macro-fracture consistently indicates the fracture class showing the main contribution of the liquid flowrate more than 10 m/d along the perforated intervals. The rock properties of this class have porosity range around 1-2% with permeability dominantly more than 100 mD. In contrast, the host-rock class is defined as a protolith/non-fractured rock. The porosity and permeability are extremely low (tight rock). This class does not give any flow contribution due to the high content of the marl or clay, the absence of the fracture, or the fractures had been re-cemented by calcite or quartz minerals. Meanwhile, the micro-fracture denotes the group of rock with porosity range around 2-10% and permeability average between 1-10 mD. In general, the flowrate coming from this fracture class was lower than 10 m/d of liquid during the flow-test. As a novelty, this proposed approach with the machine learning of SOM-clustering effectively assists us to recognize the fracture presence and its quality along the well-depth interval from the absence of the advanced technologies of image logs and production logging (PLT) measurement. Also, the defined fracture class here can take a role as a fracture facies or rock typing in terms of 3D reservoir modeling and distributed laterally based on fault-likelihood attribute and fault zone defined by distance-to-fault.
- Asia (1.00)
- North America > United States > Texas (0.68)
- Europe (0.66)
- Africa > Middle East > Egypt (0.46)
- Geology > Structural Geology > Fault (0.89)
- Geology > Rock Type > Igneous Rock (0.68)
- Geology > Geological Subdiscipline > Geomechanics (0.68)
- (2 more...)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Borehole Seismic Surveying (0.34)
- North America > United States > Texas > Permian Basin > Wolfcamp Formation (0.99)
- North America > United States > Texas > Permian Basin > Midland Basin (0.99)
- North America > United States > New Mexico > Permian Basin > Wolfcamp Formation (0.99)
- (8 more...)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Naturally-fractured reservoirs (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Faults and fracture characterization (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
- (2 more...)
This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 206027, “Naturally Fractured Basement Reservoir Characterization in a Mature Field,” by Muhammad Nur Ali Akbar, MOL Hungary. The paper has not been peer reviewed. The complete paper describes an alternative solution for identifying the presence of natural fractures, classifying them into fracture-quality-related flowability, and distributing them vertically within the well interval, and proposes a lateral distribution method for reservoir modeling. The proposed approach, using the machine-learning technique of self-organizing-map (SOM) clustering, effectively assists recognition of fracture presence and quality along the well-depth interval. Field Overview and Data Used The case study was conducted in an oil field discovered in the early 1980s in southwestern Hungary. Thirty-six wells penetrated the naturally fractured carbonate in the Triassic formation. The main lithology of this reservoir is limestone and dolomite associated with faults and exhumation breccia and marl/shale. The reservoir is saturated oil (with gas cap) with unlimited aquifer (strong water drive). The gas cap, however, is mainly composed of 85% carbon dioxide and up to 1,800 ppm of hydrogen sulfide. Generally, the oil is intermediate to heavy, with a gravity of approximately 20 °API. The reservoir rock properties of this case study are fully complex for both the pore system and its composition. In general, the matrix pore system does not significantly contribute to storativity or permeability. The effective porosity is approximately 4.2% on average. This value sometimes directs to the matrix porosity, but in this case study, high intensity of the microfracture presence behaves in a way similar to matrix porosity, a phenomenon the author terms “pseudomatrix porosity.” Moreover, the effective oil permeability value of the studied fractured reservoir is extremely high (up to 70 darcies per well-test interpretation). The permeability ranges from 1 to 2000 md in brecciated fractures or in naturally fractured rock samples. Two types of core samples were used in this study—fractured breccia and naturally fractured rock. Both types have similar behavior in terms of the porosity/permeability relationship. In this study, that relationship is not the one normally observed in clastic reservoir rock. Marl/shale content is one of the more- critical parameters, indicating low fracture quality in terms of permeability. More than 50% of the well-log data for this study were measured by Russian-type well logs, meaning that only simple electrical, gamma ray, and neutron- capture gamma logs were available. Other wells have standard triple-quad combination logs. Image logs are available only from two wells drilled in the 2000s. By considering these log-data limitations, cores, and production-test results, the study aimed to define the effective fracture locations and intervals.
- Geology > Rock Type > Sedimentary Rock > Carbonate Rock (0.55)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.46)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Naturally-fractured reservoirs (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
- Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (1.00)
Abstract We build on recent work on the petrophysical characterization of carbonate reservoirs from log and core data. Much of this work was focused on high-porosity carbonates in which the main storage is in the matrix and productivity is through connected solution vugs and high-permeability fairways. In such reservoirs, fractures do not play a dominant role in the production. These are classified as type III naturally fractured reservoirs (NFR) according to the Nelson classification. Similar reservoirs are found across much of the Middle East. However, in medium-to low-porosity carbonate rocks, fractures begin to dominate the production. These are classified as type II NFR. Fractures affect deep resistivity logs and introduce errors in the estimate of water saturation if the fracture signature is not corrected. The prolific carbonate reservoirs of the Kurdistan Region of Iraq are in this category. We have conducted a multi-well study of fractured carbonate reservoirs of Triassic and Jurassic age. The Triassic rocks are gas bearing whereas the Jurassic rocks are oil bearing. We have developed an integrated workflow to characterize both the matrix and the fractures using high-resolution nuclear magnetic resonance (NMR) logs, dielectric dispersion logs, electrical borehole images, and full-waveform acoustic logs. The mineral composition and porosity of the matrix were derived from neutron-induced capture gamma-ray spectroscopy and epithermal neutron porosity logs, and the results were validated with core data. Pore types within the matrix were evaluated using borehole NMR logs and the results were also validated with core data. The Archie m exponent of the matrix was computed from the pore partitions. Flushed zone saturation in the matrix was derived from dielectric dispersion logs and further corroborated with 3D NMR data. Full-waveform acoustic logs and electrical borehole images enable the characterization of the fractures in terms of their orientation, aperture, and permeability. Fracture porosity is calculated in multiple ways using resistivity logs and borehole images, and the best estimate is chosen depending on the validity of each method under the prevailing conditions of the borehole and formation. Finally, the effect of both the matrix and the fractures is incorporated into the computation of the Archie m parameter for deep resistivity analysis. In this manner, an accurate description of the mobile hydrocarbon content can be achieved. Finally, the predictions of produced fluid type based on the above characterization were validated with production tests. We also identified the limitations of the various methods used.
- Europe (1.00)
- North America > United States > Texas (0.67)
- Asia > Middle East > UAE (0.46)
- Asia > Middle East > Iraq > Kurdistan Region (0.25)
- Geology > Mineral (1.00)
- Geology > Geological Subdiscipline > Geomechanics (0.69)
- Geology > Petroleum Play Type > Unconventional Play > Fractured Carbonate Reservoir Play (0.60)
- Geology > Rock Type > Sedimentary Rock > Carbonate Rock (0.48)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Borehole Seismic Surveying (0.76)
- North America > United States > Texas > Permian Basin > Yeso Formation (0.99)
- North America > United States > Texas > Permian Basin > Yates Formation (0.99)
- North America > United States > Texas > Permian Basin > Wolfcamp Formation (0.99)
- (24 more...)
Abstract This challenging reservoir characterization case study is defined by the interaction between two reservoirs with different production mechanisms: a fractured basement reservoir and an overlying sandstone reservoir. The existing static geologic concept has been significantly enhanced by integrating pressure data from a unique three-year shut-in period to aid modeling of fractured reservoir connectivity. Previously, the seismic dataset was predominantly used to model the fault and fracture network and guide well planning. In the current approach, the full field data set, including all drilling parameters and new reservoir surveillance data were integrated to address uncertainty in the connected hydrocarbon volume and the relative importance of each production mechanism. The result is a reservoir management tool with which to test re-development concepts and effectively manage pressure decline and increasing gas/oil ratio (GOR) and water production. To achieve a fully integrated history matched model, the first step was to make a thorough review of the existing detailed seismic interpretation, vintage production logging tool runs (PLT's), wireline logs (including borehole image logs (BHI)) and drilling data to find a causal link between hydraulically conductive fractures and well production behavior. In parallel, a material balance exercise was run to incorporate the new pressure data acquired during the field's shut-in period. The results of the material balance analysis were combined with seismic and well data to define the distribution of connected fractures across the field. Additionally, the material balance analysis was used to determine the connected hydrocarbon volume, the distribution of initial oil in-place and the relative hydrocarbon contribution from each production mechanism. The field is covered by multi-azimuth 3D seismic and 43 vertical to highly deviated development wells, providing significant static and dynamic data for characterizing the distribution of connected fractures. Despite this high quality, diverse and field-wide dataset, prior modeling iterations struggled to sufficiently describe the production behavior seen at the well level. This has resulted in a major challenge to predicting the production behavior of new development wells and planning for reservoir management challenges. Capturing the complex interaction between production variables (including lithology, matrix versus fracture network, geomechanical stresses, reservoir damage and pressure depletion) at a field level instead of at an individual well level resulted in a unified static and dynamic model that reconciles all scales of observation. This oilfield represents a unique reservoir characterization opportunity. The result is a key example of how iterative, integrated geological and engineering driven reservoir modeling can be used to inform the development in a complex, mature field. This case study provides an excellent analogue for the reservoir characterization of other fractured Basement fields and/or Basement-cover reservoir couplet fields in the early to late phases of their development.
- Europe (1.00)
- Asia > Middle East > Yemen > Shabwah Governorate (0.48)
- Proterozoic (0.68)
- Phanerozoic > Mesozoic (0.68)
- Geology > Structural Geology > Fault (1.00)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Structural Geology > Tectonics > Extensional Tectonics (0.68)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.55)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Seismic Interpretation (0.88)
- Europe > United Kingdom > Atlantic Margin > West of Shetland > Faroe-Shetland Basin > Rona Ridge > Block 205/26b > Lancaster Field (0.99)
- Europe > United Kingdom > Atlantic Margin > West of Shetland > Faroe-Shetland Basin > Rona Ridge > Block 205/22a > Lancaster Field (0.99)
- Europe > United Kingdom > Atlantic Margin > West of Shetland > Faroe-Shetland Basin > Rona Ridge > Block 205/21a > Lancaster Field (0.99)
- (12 more...)