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EAGE Conference on Reservoir Geoscience
- Conference date: December 3-5, 2018
- Location: Kuala Lumpur, Malaysia
- Published: 03 December 2018
21 - 40 of 87 results
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Gravity And Subsidence Monitoring For Production Optimization And Improved Reserve Estimation Of Gas Fields
By O. EikenSummarySurface gravity and subsidence monitoring for improved reservoir management are rapidly developing. On land sub-cm precision can be obtained with various techniques, and at the seafloor by using water pressure measurements. The surface movements are mostly caused by changes in fluid pressure and can be inverted for the product of reservoir pressure change and compressibility. Gravity monitoring is now routinely done with a precision of 1–2 µGal. The low density of gas makes water influx in gas reservoirs a primary goal for gravity monitoring. Combining reservoir pressure with gravity data, the remaining gas will be better determined.
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Characterization Of Basement Reservoir Lithology Using Mineralogical And Geochemical Approach: Example From Malay Basin
Authors S.N. Cheng, N. Pendkar, M.R. Anuar, R. Danial, R. Roslan, C. Magnier and V. TharmalingamSummaryThe known plays in the Malay Basin has been well explored, developed, and produced with the exception of ‘fractured basement’ which still remains underexplored. Wells drilled to-date into the fractured basement in the Malay Basin yielded variable results.
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Role Of Seismic Attributes In Reserve Estimation
Authors R.A. Mohamed Ghozali, A.T. Patrick Panting, N. Zakaria and H.N. NguyenSummaryIn Oil & Gas - Exploration and Development endeavors, there is no doubt that seismic data plays a huge and important role. In fact, it is considered to be the primary tool when we attempt to understand what we have in the subsurface. Seismic data however, is not that simple and has its own limitations. Seismic resolution for example is important to seismic interpreters and knowing the tuning thickness will help us know how much of the reservoir can be imaged vertically. In cases of low resolution, the thinner bed might not be imaged or can be seen only partially, causing the thin hydrocarbon bearing reservoirs to go undetected or unnoticed during seismic interpretation. The aim of this paper is to demonstrate using a case study from the Malay Basin, how seismic attributes may help in interpretation and identifying reservoir boundaries in areas below the tuning thickness and where interference from the above bed causes more challenges.
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Facies-Based Inversion Through The Asset Lifecycle
By S.K. ChengSummarySeismic lacks low frequencies, so for an absolute seismic inversion (which allows us to be quantitative!) a so-called Low Frequency Model (LFM) is required. Starting from an empty LFM, we would of course like to post Sand Vp values where there is Sand, Shale Vp values where there is Shale, etc. (for a minimum of 3 impedances and for all facies expected).
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Streamlining Petrophysical Workflows With Machine Learning
Authors L. MacGregor, R. Keirstead, N. Brown, A. Roubickova, I. Lampaki, J. Berrizbeitia and M. EllisSummaryThe oil and gas industry is not short of data, in the form of wells, seismic and other geophysical information. However, often because of the complexity of workflows and the time taken to execute them, only a fraction of this information is utilized. Making better use of information, using modern data analytics techniques, and presenting this information in a way that is immediately useful to geologists and decision makers has the potential to dramatically reduce time to decision and the quality of the decision that is made. Here we concentrate on using machine learning approaches to streamline petrophysical workflows. However, to do this requires a rich and diverse training dataset of wells that have been consistently processed for geophysical analysis. The work discussed in this paper has focused on the estimation of clay volume, determination of mineral volumes and determination of porosity and water saturation. A variety of machine learning techniques and algorithms have been tested to find the one most suited to this application. Initial analysis is regionally focused, but we plan to investigate whether the approaches and models developed can be generalized across regions, basins and geological settings.
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Elasticdocs As An Automated Information Retrieval Platform for Unstructured Reservoir Data Utilizing A Sequence Of Smart Machine Learning Methods Within A Hybrid Cloud Container
Authors N.M. Hernandez, P.J. Lucanas, I. Panganiban, C. Mamador and C. YuSummaryThere is a tremendous amount of information available and stored in digital geoscientific documents and published reports in the energy industry. These documents contain a distillation of reservoir information from diverse discipline of geologists, geophysicists, petrophysicists and drillers, that are stored in unstructured format, which find further use in succeeding reservoir modeling stages. In particular, national data management repositories and oil companies hosts these huge amounts of historical well reports containing information such as lithology, hydrocarbon shows, and other reservoir data. Due to the large volume, vintage variety, and non-standardized formats, extraction of valuable information that are used as inputs for interpretation, is an arduous, very time-consuming task. Our solution is to develop ElasticDocs a machine learning-enabled platform in a hybrid cloud container that automatically reads and understand hundreds or thousand of technical documents with little human supervision through a smart combination of machine learning algorithms including optical character recognition (OCR), elatic search, natural language processing (NLP), clustering and deep convolutional neural network. The platform uses a hybrid, 2-tier data service architecture leveraging on the strength of both the strength of local servers and cloud to enhance data security, integrity, and accessibility.
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Seismic Multi-Attribute Volume Classification: Case Study From Malaysian Reservoir
Authors M.M. Jalil, Y. Khairil Amin, S. Isa and H. OthmanSummaryIn complex reservoir, individual seismic attributes are usually insufficient to delineate in detail stratigraphic features of a specific target. Seismic Multi Attributes Pattern Recognition or “SMART” is an advanced techniques for application in reservoir study. Generating supervised and unsupervised classified maps through seismic pattern recognition provides and effective method to map stratigraphic features. It reveals details of underlying geologic features and help in the interpretation of facies changes in reservoirs.
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Litho-Fluid Characterisation Of Fluvio-Deltaic Gas Reservoirs Through Ava Deterministic And Stochastic Seismic Inversion
By A. ContrerasSummaryA state-of-the-art Amplitude-versus-Angle (AVA) inversion methodology is described in this case study to quantitatively integrate partially-stacked seismic data, well logs, geologic data and geostatistical information. Deterministic and stochastic inversion algorithms are used to characterise Intra-Triassic Mungaroo gas reservoirs located in the Carnarvon Basin, Western Australia. AVA deterministic and stochastic inversions, which combine the advantages of AVA analysis with those of seismic inversion, have provided quantitative information about the lateral continuity of the Fluvio-Deltaic reservoirs as well as the delineation of the gas reservoirs, based on the interpretation of inverted elastic properties and lithology and fluid-sensitive modulus attributes. AVA stochastic inversion provides more realistic and higher-resolution results than those obtained from analogous deterministic techniques and allows for uncertainty analysis. The quantitative use of rock/fluid information through AVA seismic data, coupled with the co-simulation of elastic/petrophysical properties, provides accurate 3D models of engineering properties such as porosity, volume of shale, and water saturation which can be directly used for static model building.
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Fine Scale Clastic Reservoir Characterisation And Uncertainty Quantification—A Case Study Offshore Sarawak
Authors R. Doshi, N. Vargas, O. Colnard, S. Saad El Kurdy, A.L. Yahya and C.K. TanSummaryThis paper presents a stochastic inversion case study carried out on a mature field, offshore Sarawak. This study is an attempt to overcome a few data limitations. Firstly, the resolution of the seismic data at the target depth is well above the required resolution of 5–10 m. Secondly, localised poor quality pockets in the seismic data created uncertainties in the well depth to time relationship. Also, an initial test of stochastic inversion showed that the number of surfaces required to constrain the target interval were not sufficient and created incorrect geobodies. This paper details how these issues were addressed.
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Application Of Seismic Inversion Workflow Guided By Depth-Dependent Rock Physics Trends: A Qi Study In Pm-3 Caa
More LessSummaryApplication of Seismic Inversion Workflow Guided by Depth-dependent Rock Physics Trends: A QI study in PM-3 CAA
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Reviving Un-Tapped Potential In A Brown Field Through Geophysical And Reservoir Model Evaluation
Authors N.A. Mohamad Radzi, R. Hardiani, M.Z. Zamanshah, A.H. Mustafa, A. Khalil, Z. Ishak and A. RoySummaryThis paper will demonstrate the best practices in Geophysical and Reservoir Model Evaluation for identifying remaining untapped oil opportunities. A 4-Component 3-Dimensional Ocean Bottom Cable (4C 3D OBC) seismic survey was acquired in 2015 and was used as input in building the reservoir model and used for identifying the remaining oil location in a brown field in Field Tango. This led to a more advanced management through placement of water injection, infill wells and new oil producers in this field to sustain and increase production.
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Which Fault Matters: Evaluation Of Reservoir Compartmentalisation By Integration Of Borehole Image And Real-Time Isotope Data Δ13C1
Authors N. Ha, C. Murlidhar, A. Brem, V. Vevakanandan and T.T. ZhangSummaryShell Malaysia has drilled 11 development wells targeting two reservoirs (R1 and R2) in a Deepwater Field (M field) offshore North West Borneo. M field is a complex faulted 4-way dip closure, comprising a turbiditic depositional environment.
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Linking The Diagenetic Evolution To Poroperm Development In A Paleozoic Carbonate Reservoir Analog, Northern Vietnam
Authors H.A. Nguyen, T.A. Vu, T.T.T. Tran and T.S. NguyenSummaryA lot of exploration wells have been drilled to test “buried-hill” plays in fractured Paleozoic carbonates in offshore northern Vietnam with either dry holes or showing low flow rates. To better understand diagenesis-related poroperm development and how can we target more successfully in this complicated reservoir, a detailed geological characterization of fractured Paleozoic carbonates was undertaken in a quarry outcrop in the Northern Vietnam. This work integrates the results of detailed mapping and interpretation of lithologies and fracture orientations, along with detailed petrographic and isotopic analyses and leads to the following conclusions: (1) Significant levels of poroperm in fractured Paleozoic carbonates in the region are mostly confined to NE-SW fracture sets created and enlarged in the telogenetic realm relating to uplift in a stress field created by movement of the Red River Fault. (2) Equivalents to this style of diagenesis likely occur in subsurface as potential fractured Paleozoic reservoirs in the nearby offshore. (3) Successfully exploring and developing such reservoirs will require directional (not vertical) wells and a better rock-based understanding of the controls, orientations, timings of major fracture events (requires outcrop and core-calibrated FMI interpretation). (4) Poroperm predictions in subsurface counterparts require an improved understanding of fluid evolution and the relative timing of the various diagenetic events that can occlude or enhance porosity and permeability in both matrix and fractures (requires detailed petrographic study tied to texture-aware isotope sampling of cuttings or core).
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Controlling Factors For Reservoir Quality In East Balingian, Sarawak
Authors A. Noorhashima and T. PrasetyoSummaryThis study aims to understand the controls of the reservoir quality in the East Balingian, Sarawak. Data integration from cores and cuttings (petrography, XRD, porosity & permeability) as well as temperature and pressure data from 23 wells are used. The result observed that most of the wells show porosity reductions (going less than 10%) starting at 2000–2500 mSS and this serves as the crictical depth for porosity preservation in the study area. It was found that this reduction in reservoir quality are affected by mechanical compaction, overpressure, chemical compaction (temperature & diagenesis) and facies grain sizes and clay content. The improved understanding gained from this study is hoped to be used as a guide for near future exploration campaign in the less explored areas in East Balingian basin.
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3D Paleo-Environmental Facies And Petrophysical Properties Of Mangahewa Formation, Maui Gas Field, New Zealand
By A.E. HAQUESummaryMaui Gas Field is the largest producing field in New Zealand having Mangahewa Formation as the thickest reservoir of this field. According to the study Marginal marine was interpreted to be the dominant depositional environment of the formation as a whole having about 64% of depo-facies; whereas shallow marine environment comprised about 29% and offshore comprises 7% of the depo-facies modeled within the Mangahewa Formation, Maui Gas Field. Paleoshoreline reconstruction of the facies modeled that ttransgression occurred from older deeper to the younger shallower layers within the model. Paleoshoreline was interpreted to have a broad North-East to South-West trend within the model along with their internal migration over time.
Whereas the petrophysical model of the formation correlated positively with the paleo-depositional model and petrophysical maps of Mangahewa reservoir parameters reveal that, the most favourable location for the producing reservoir is the east-central part of the gas field.
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Successful Integration Of Sampling While Drilling And Geomechanical Analysis In Unconsolidated Reservoir: A Case Study From Sarawak, Malaysia
Authors I.L.T. Ong, A.K.L. Ng, N. Hardikar, A. Khalid, J. Pragt, A. Khaksar and F. AdegbolaSummaryFirst LWD water sampling work in Malaysia
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Geomechanical Modeling Of Thermal Effects On Pore Pressure Prediction And Wellbore Stability In Hpht Wells
Authors A. Chatterjee, A. Ghosh and S. BordoloiSummaryThe integration of geomechanical modeling with understanding of geological control on overpressure mechanism helped the well designer sets his/her expectations in the planning phase, enabling a more proactive approach for flawless execution during the drilling phase. The well was successfully drilled to the desired depth despite a predicted drilling margin of only ∼1.0 ppg, reducing non-productive time (NPT).
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Accurate Geomechanical Sanding Prediction, Two Case Studies From Offshore South And South East Asia With Years Of Production
By A. KhaksarSummaryThis presentation highlights the essential elements of an integrated sand management approach with a focus on geomechanical sanding risk evaluation for sand control and completion decisions. The presentation will include two recent case studies from offshore South East and South Asia with different geological settings and well operation conditions, both with several years of production history and observations. The two case studies demonstrate the validity of geomechanical assessments conducted at early field life that are verified later following 10–15 years of hydrocarbon production with different outcomes and observations.
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Geology To Geomechanics Integrated Workflow For Better Production Risk Management
Authors C. Cosson, S. Ducroux and L. Van den BrulSummaryComprehensive geomechanical studies are key to mitigate risks from in-situ stress changes due to oilfield drilling, completions and production operations. Today however, most geomechanical models used in these studies lack the geological integrity required to derive reliable decisions. One major contributor to this limitation is the alterations to data and assumptions as they get passed from one discipline to another; very often a symptom of a poor cross-domain collaboration. A geomechanical specialist for example gets his input 3D model from the reservoir engineer, but operates usually independently from the geophysicist or the geologist who interpreted the initial data. This disconnect between disciplines is seen as both a work culture problem and a technology problem. This paper will address the technology aspect by introducing new advancements to geomechanical workflow integration through the use of a shared structural model. This model is constructed by honouring available data without unwarranted simplifications. It is then used by geoscientists across the board including geophysicists, geologists, reservoir engineers and geomechanical specialists to derive fit-for-purpose and consistent numerical models. For the geomechanical workflow, structured and unstructured grids are created directly from the shared structural model honouring all interpreted structural and stratigraphic features critical for a proper assessment of stress changes in the Reservoir.
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State Of The Art In Petrophysical Modeling Of Low Resistive Low Contrast Pays (Lrlc) Using Ideal Resistivity Model
By H. HassaniSummaryNowadays Low Resistive Low Contrast pays (LRLC) are forefront of mature-field secondary objectives where production from conventional reservoirs get lesser and lesser. Although LRLC reservoirs have been under production for many years, knowing reservoir complexity mainly at volume and flow capacities are still big challenges. Lithology is one of the element, which can carry some portion of reservoir complexity. Among the possible scenarios, shale plays a different role; Understanding the shale behavior and its distribution patterns is a key to improve the reservoir characterization and consequently unlock potential unseen volumes. In the absence of a well defined distribution model, an integrated approach of forward modeling and inversion is also impractical for the accurate evaluation. Majority of conventional approaches unable to address reservoir complexity due to log resolution constrains. This paper aims to introduce new approach, as a tool, to qualitatively determine thin-bedded sand characteristics, which can be used as an integral part of low-resistive techniques. It implements ideal resistivity-base model (RT-Model) to evaluate shale distribution in clastic reservoirs. The process couples the deep resistivity with gamma ray measurements in new laminar gauge to properly determine not only corrected shale volume but also distribution pattern independent of advance log measurements. Based on the result the method is able to quantify bed thickness smaller than a feet (2 to 4 in) that is actually beyond conventional log resolution. Corrected shale volume and sand resistivity are main products while net sand porosity and fluid saturation are secondary products derive through workflow optimization practices and uses inputs from new lamination model. Resistivity-base porosity shows better consistency with core data where traditional approach failed to match core trend in highly laminated section.
Outcomes has been finally verified with hard evidences and direct measurements like image log, production profiles and core data. Compression shows encouraging results at both well and field scales. At well level, RT-Model products has been fully align with direct measurements and at field scale, results have been fully supported by dynamic model where enhanced volume and flow capacity from RT-Model are closely tied with expectation from the model.
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