Accurately characterizing fracture network morphology is necessary for flow simulation and fracturing evaluation. The complex natural fractures and reservoir heterogeneity in unconventional reservoirs make the induced fracture network resulting from hydraulic fracturing more difficult to describe. Existing fracture propagation simulation and fracture network inversion methods cannot accurately match actual fracture network morphology. Considering the lightning breakdown similar as fracture propagation, a new efficient approach for inversion of fracture network morphology is proposed. Based on the dielectric breakdown model (DBM) for lightning breakdown simulation and similarity principle, an induced fracture propagation algorithm integrating reservoir in-situ stress, rock mechanical parameters, and stress shadow effect is proposed. The fractal index and random function are coupled to quantitatively characterize the probability distribution of induced fracture propagation path. At the same time, a matching rate function is proposed to quantitatively evaluate the fitting between fracture network morphology and the micro seismic data. Combined with automatic history matching method, the actual fracture network morphology can be inverted with the matching rate as objective function. The proposed approach is applied to fracture network simulation of mult-fractured horizontal wells of shale oil reservoir in China, and the fracture networks from inversion fit well with the micro seismic data. A simulation of 94 fractures in the 32 section of Well X2 shows that the well propagates more obvious branch fractures. The single-wing fracture network communicates approximately 200m horizontally and approximately 10m vertically. In single fracture flow simulation, it is necessary to consider the influence of complex fracture network morphology, but when simulating fluid flow for a single well or even a reservoir, only the main fracture needs to be considered. This paper proposes an induced fracture propagation algorithm that integrates reservoir in-situ stress, rock mechanical parameters, and stress shadowing effects. This algorithm greatly improves the calculation efficiency on the premise of ensuring the accuracy of induced fracture network morphology. The approach in this paper provides a theoretical basis for flow simulation of stimulated reservoirs and optimization of fracture networks.

Drill cuttings are a valuable source of information about lithology and wellbore condition. Although an abnormally high number of cuttings would indicate some sort of failure at the wellbore wall, a detailed analysis of cuttings can help to identify the type of rock failure. Cavings, fragments that are relatively larger and of different shape compared to normal cuttings, can be used to decode critical information about the wellbore geometry and formation pressure. Cuttings analysis is most useful in absence of direct indicators of wellbore condition such as caliper, image logs, or logging-while-drilling (LWD) data, but even in presence of such data, cuttings analysis can be used to corroborate the interpretations with direct measurements. Several mechanisms, such as underbalanced drilling, pre-existing weak planes, stress relief, or even the drilling process itself, can lead to production of cavings. Examining the cavings to interpret wellbore instability and mechanisms responsible for it is an expert's job and requires a good overall understanding of the prevailing geology, geomechanical principles, drilling procedure, and drilling tools. Identification of wellbore failure during drilling provides a better chance of immediate remedial action, even before a wireline logging program is executed. Differentiating cuttings generated by the drill bit from cavings created by the wellbore failure is not an easy and straightforward task due to a variety of bits and phenomena involved in the generation of cuttings. The first step in this analysis is to broadly define the different types of cavings based on their shape and size. Then, we move to the basic key features of these cuttings, and, finally, provide the remedial action plan for each type. Drill cuttings analysis was successfully applied to improve hole condition in real time for two wells drilled in the Western Offshore basin, India. One case study illustrates the importance of mud chemistry over the mud weight being used to drill. The second case study underscores the interpretation of shear failure as the reason for cavings from cuttings morphology analysis. In both the cases, timely intervention integrated with the identification of prevailing drilling issues in real time helped in understanding the mud system and its effects on the wellbore. The novelty of this approach lies in the deep understanding and geomechanical application of cavings in providing timely and cost-effective recommendations to optimize drillability in both the presence and the absence of LWD data. The results can be used during the well-planning stage of future wells and during drilling to improvise mud chemistry or to identify required increase in mud weight to avoid breakouts related to chemical instability or shear failure even though the pore pressure profile may not necessarily require any further increase in the mud weight.

Within the Oil and Gas industry, real-time data streaming is essential to conduct high-impact analytics. The Energistics Transfer Protocol (ETP) enables data to be streamed with low latency. The current mechanism of querying the data transferred through ETP is cumbersome, especially for the domain user who wants to realize the full benefits of this protocol. Energy Query Language (EQL) is a domain-specific language (DSL) for querying data which is streamed through ETP with a concise SQL-like structure in real-time. The EQL System (EQLS) provides the ability to query streaming data in real-time across various platforms and business applications, as well as in web or analytics platforms like Python. The EQL grammar is simple enough to reduce the complexity of the current mechanism used for querying and aggregating real-time data. Built with components that can support advanced analytics requirements including big data analytics, EQLS is future-proof.

In this paper, we present for the first time, a classification system for naturally-occurring gas hydrate deposits existing in the permafrost and marine environment. This classification is relatively simple but highlights the salient features of a gas hydrate deposit which are important for their exploration and production such as location, porosity system, gas origin and migration path. We then show how this classification can be used to describe eight well-studied gas hydrate deposits in permafrost and marine environment. Potential implications of this classification are also discussed.

Data bases of numerous oil and gas companies embrace very promising potential for more informed decision-making processes. Furthermore, there is an exponential growth in the influx of generated data from an escalating parade of systems encompassing Enterprise Resource Planning (ERP), machine instrumentation, sensory networks, and escalating mixed-media and different unlabeled data. Despite that, extracting meaningful value from zettabyte-sized datasets remains problematic given the uncontrollable wealth of data and its subsequent noise caveats. Amongst those data warehouses, are a multitude of textual information. Accordingly, Text mining has garnered worldwide interest, as it is a crucial phase in the process of knowledge discovery automatically extracting unstructured to semi-structured information. The following survey covers Text Mining methods and approaches to explain their effectiveness in information retrieval from textual databases from various sources. Moreover, the situational types where each technique may be beneficial are explored.

As the adoption of the high-speed development of the information technology and continuous improvement of industrial technology, huge amount of statistical data and statistical documents are accumulated in environment-safe and environment-friendly field. The big data technology drives the attention points in the safety science field turn to the data and the exploration of the security management mode established on analysis of the data. When the big data oriented thinking and mode are used, the safety management knowledge underlines the hidden danger data in production safety is disclosed, and precision application of the safety management will be promoted. The hidden danger data of safe production is stored in text form, and data mining and machine learning model can’t deal with these non-structured (or half-structured) information directly, so it is necessary to deal with the text data through Natural language processing (NLP), and then use the data mining method to excavate the rules information. First of all, the words in the text are recombined through technologies such as Chinese word segmentation, part-of-speech labeling, named entity recognition and the like, the word of the combined vocabulary is marked, and the named entity is further identified. Secondly, the structured problem disclosing database is constructed through three steps including keyword mapping and extraction, data cleaning and integration, data selection and transformation. What’s more, by using data mining technology such as data stream sliding window model, association analysis and change mining algorithm, this paper constructs the related hidden danger analysis method. By means of mining association rules of the current hidden danger data, releasing the related type, the existence possibility and the change pattern of hidden danger and so on. Finally, the information is visualized and analyzed. In this paper, the data mining of 10,387 safety hidden danger samples of a refinery enterprise in 2012-2017, obtained 1091 association rules, constructed 5 kinds of associated hidden danger transformation mode: the emerging mode, attenuation mode, relation change mode, result transformation mode, new adding mode. These modes are summed up the following conclusions: (1) in view of the safety hidden danger data of petroleum and petrochemical industry, this paper analyzes the language characteristics of the domain corpus, and first forms a professional dictionary with industry characteristics; (2) using Eclat association analysis algorithm to excavate the association rules between hidden danger data, and classify the rules, which mainly focus on the pipeline, valve, safety valve and other parts; (3) after analysis of the hidden danger, the leakage of the bearing box, blind plate missing, the length of the coupling shield is too short, the discharge port setting height does not meet the requirements, the automatic valve failure, the export pressure gauge real fluctuation are six problems for the second half of 2017 new problems. By excavating the potential value of the hidden danger data, the hidden danger checking work is further optimized and improved, and the enterprise is guided to carry out targeted hidden danger checking, the centralized optimization of services is realized, the accurate application of safety management is promoted, and the safety and environmental protection management and risk control level are improved.

Corrosion of oilfield equipment and processing facilities is a common occurrence that can pose a serious threat to the integrity of the facilities. When failures occur, the leaking substances can be very dangerous to lives and be very harmful to the environment for a long time. Direct total costs due to corrosion, its preventive measures, repairs and litigations are in the billions of dollars each year. Identifying the type of corrosion is the first step in the analysis and prevention of corrosion-related failures. Visual inspection of the pit morphology can give insights into the type of corrosion that is occurring. This paper describes how to identify the corrosion mechanism based on the pit orphologies. Descriptions and diagrams of pit morphology of each type of corrosion along with actual pictures of the typical corrosion or failures are included.

Abstract The Lower and Middle Ordovician carbonate karstic reservoirs form an important type of reservoirs in the Tarim basin, the largest inland basin in China. Karstic feature characterization along with infill identification provides a great opportunity to delineate the distribution and connectivity of collapsed-cave systems. Based on carbonate karst concepts, this paper presents an integrated approach to characterize collapsed-cave systems and to map the geomorphology and distribution of karstic drainage components. Seismic amplitude and geometric attributes are used to identify karst features such as collapsed-cave complexes, conduits and infiltration or dissolution zones. A multivariate attribute classification technique is applied to generate karst seismic facies that highlight these features. Clustered karst features are sampled into the grid model to construct a 3D architecture model of collapsed-cave systems. This model eventually incorporates all clustered features, revealing their spatial distributions, inherent complex shapes and lateral connectivity. In the case of preserved collapsed-cave systems become disconnected and occluded as a result of infilling and roof collapsing, collapsed-cave systems need to be further calibrated in order to locate infill drilling and identify dynamic compartments. The seismic acoustic impedance attribute facilitates the identification of infill within collapsed-cave systems because chaotic breakdown breccias and cave-sediment fills have an impedance lower than that of the host limestone resulting in a significant impedance contrast. Incorporating the impedance attribute with the architecture model, the bodychecking technique is applied to searching for connected cells to extract karstic drainage components. The geomorphology and distribution of individual components can be mapped. Integrating reservoir production data and borehole imaging logs, the drainage components can be evaluated and sorted. The case study is addressed to illustrate applications of these technologies and their efficiency. Introduction Karst systems in the Tarim basin are formed by subaerial exposure and karstification during a long period of time from the Lower to the Middle Ordovician. Loucks (1999) showed that most karst reservoirs are not products of isolated collapsed passages, but instead are a product of coalesced collapsed-paleocave systems hundreds to several thousand meters across and thousands of meters long. Identifying karst related products in cores, i.e. cements and fabrics, dissolution porosity and specific features, can help to recognize and describe karst systems. The origins of coalesced, collapsed karst systems and associated product features have been studied (Kerans, 1988; Loucks and Handford, 1992; Loucks, 1999; Loucks et al 2004; McDonnell et al, 2007). Sags associated with collapse were good indicators to locate the coalesced collapsed carbonate Karsts (Lucia, 1996). Loucks et al. (2004) defined the three-dimensional, interwell-scale architecture of a Lower Ordovician Ellenburger coalesced, collapsed-paleocave system through the integration of ground-penetrating radar (GPR), shallow-core, and outcrop data. Karst systems have complex features and tend to have pronounced lateral and vertical heterogeneity, especially when multiple phases of karsting and burial are involved (Loucks and Mescher, 1997; McMechan et al., 1998; Loucks, 1999).

Abstract Lab capillary pressure Pc measurements are routinely performed on core plug samples. Applications of Pc curve measurements are mainly to derive some relationships between water saturation Sw and the height H above the Free-Water-Level FWL. The resulting correlations can then be cross-checked vs. the Elogs-derived Sw so as to confirm the overall consistency of the Sw model. Ultimately, the Sw - H relationship can be used as input to the 3D model. In addition, screening of Pc - Sw relationships often allows defining robust rock-types, based on observation of Pc clusters vs. the sample porosity, permeability, mineralogy and geological facies. In the case of MICP, the rock-type classification may be further enhanced by looking at the Pore-Throat-Radius PTR distributions, related to the derivative of the Pc curve. Several methods to derive Sw - Pc relationships and classify Pc clusters are possible (e.g. Leverett, Thomeer, Johnson, Cuddy, Skelt, ..) and have been documented and published in the past. In this paper, we make a synthetic review of the pros and cons associated to each Pc classification method. Eventually, we propose an innovative way to take the best of several known Pc classification methods in defining a straightforward technique to derive robust Pc clusters and equations.

Abstract Commonly, only very limited amounts (10–200 g) of sample can be retrieved by bailers or on the filter screens at well heads and the usual evaluation is simply XRD, XRF and occasionally, SEM analysis to identify basic mineralogy. Unfortunately, these very small and poorly differentiated samples are the only evidence production engineers have to evaluate significant issues with completion and drilling chemistry. But, a geologist's eye, and polymorph chemistry can use these small samples to dictate a story. In a recent study, meticulous sample preparation and visual sample evaluation, combined with XRD, thin section petrography, crystal morphology, and evaluation of polymorphic and formation water chemistry have been intertwined to evaluate scaling history in several wells in a high temperature, high pressure gas condensate field. The study was able to identify various polymorphs of CaCO3, (including Mg-calcite and aragonite), and assign them to quiescent vs. dynamic precipitation regimes, through the assessment of morphological features (including botryoidal, dendritic and flos ferri morphologies of aragonite). In addition, multiple stages of barium sulfate (BaSO4) and sulfate/carbonate co-precipitation were identified. An additional fecarbonate phase, siderite (FeCO3), was identified. Using thin section petrology, mineralogy, and a thorough review of drilling and completion operations, the unique scale formation history of these wells was traced, and issues were identified with long-term post-completion shut-ins while waiting for tie-in of manifolds to pipelines. Issues were identified with CO3 -2 pH buffers in formate based completion and drilling fluid interactions with high calcium formation brine, which migrates to the well bore by ionic diffusion and counter-current imbibition. The identification of this previously un-suspected damage mechanism has led to modification in completion fluid formulations to eliminate future events, and improve post drilling PI on wells drilled in the gas fields in question. It highlighted the requirement for a scale control program which is being developed to be concurrent with new well drilling and completion. Finally, the study highlights the need to evaluate fully the components of drilling, completion and stimulation fluids, both individually, and in combination-To be sure to fully assess the risk of formation damage, even when using a welltested and proven industry fluid. The phrase "doveryai, no proveryai" ("trust, but verify") takes on a new meaning (with due respects to US Pres. R. Regan).

Abstract The heterogeneity in carbonate rocks, made it hard for Geoscientists and Reservoir Engineers to define a universal classification methodology that is able to honour the critical reservoir static properties. Most classifications, like, lithofacies, capillarity and textural methods have based their rocktyping concept on one or two static properties, then tried to find an analog to other static properties to cluster or group them, then worked to populate the rock types across the whole field. However, from field observations and experiences of utilizing these conventional techniques, it was obvious that they suffered from several gaps, like inability to have the properties analog consistent throughout the whole reservoir. Moreover, the groups or clusters have big dispersion that produced overlaps, and then theoretically they could not fully honour the physics and rock properties links. Therefore, in this study, rock typing is made to honour static properties all together through changing the classification concept to resolve the gaps of the traditional methodologies. The ultimate objective of all reservoir characterization and rock classification is to enable building geological and simulation models, with optimum honouring of rock properties. To achieve this objective, the established framework in this research is based on analyzing the effects of each of the rock properties on another and the value and impact that each can add to the models most critical parameters. By this technique, the gap of pore and pore-throat network is resolved through Multiple Properties Intersection. This Integrated Carbonate Rock Typing technique starts with capturing the heterogeneity of carbonate rock by generating matrix of core permeability, capillary pressure (end point, threshold pressure and Plateau), pore-throat size distribution and porosity. Then intersecting this matrix to construct weighted links between these properties and identify unique groups. Resulted classes are novel carbonate rock type classes that entered to feedback analysis node to explore and validate the logic of linked physics to tune the classes'thresholds and assure no overlap between any of classification properties. Finally for utilizing this technique in non-cored wells, an analog with logging data is structured through novel permeability, capillary pressure and saturation function called the C-Function to be the replacement of the J-Function in Carbonate.

Abstract Miocene carbonate reservoirs may contain appreciable amount of microporosity in grain, cement or matrix. Depending on the crystallometry and morphometry of micrite particles, microporosity can vary both in amount and in nature. Different kinds of micrite microtextures may produce different types of microporosity. This study proposes a classification of micrite microtextures and microporosity. Four different types of micrite microtextures are classified in this study; these are rounded micrites, subrounded micrites, microrhombic and polyhedral micrites, and compact anhedral micrites. Four different types of micropores are classified based on their pore sizes. These are very fine, fine, medium, and coarse micropores. The classification of microporosity allows its occurrence in carbonate reservoirs to be explained depending on micrite microtextures. The classification of micropores in terms of their micrite microtextural occurrence lead us to define the micropores that are contributing to the permeability of the reservoirs and allow fluid flow in carbonates. The classes of micropores together with the corresponding micrite microtextures of their occurrences help to define the potential reservoir rocks in terms of micrite microtextures. Introduction The complexity in pore systems of carbonates is mostly due to the biological origin of carbonate sediments and their chemical reactivity. Since more than half of the earth's hydrocarbon reserves are contained within pore systems in carbonate reservoirs, studying these pore systems has always been an integral part of hydrocarbon exploration. Large uncertainties in petrophysical properties of carbonates are due to wide variations in pore type, pore shape, and interconnectivity (Knackstedt et al., 2008). Porosity in carbonate rocks can be divided into two main pore systems: macropore, and micropore system. These pore systems are divided on the basis of the pore size and their relative contribution to fluid flow in the rock. Micropores are important in that they can provide a pathway connecting microporous grains to one another and to macropores (Cantrell and Hagerty, 1999). Different definitions of microporosity have been proposed and applied in the literature (Figure 1). For our study we defined micropores as all pores that are less than 10 microns in maximum diameter. Microporosity can occur in grain, matrix or cement of carbonate reservoirs. The most widely used classifications of porosity in carbonates are those of Choquette and Pray (1970) and Arve Lønøy (2006). Choquette and Pray (1970) classified pores according to the fabric selectivity of the sediments, whereas Arve Lønøy (2006) classification is texturally derived mostly from Choquette and Pray (1970) and incorporates pore-size differentiation. A classification scheme for micropores that can relate to the abundance, occurrence, and distribution of microporosity, could provide a framework for better understanding of flow-related properties of microporous Miocene carbonate reservoirs of offshore Sarawak. The study of microtextures of micrites is a key factor for understanding the abundance, occurrence, and distribution of microporosity in carbonates.

Abstract In any reservoir modeling exercise, accurate estimation of initial water saturation is crucial to determine the in-place hydrocarbon volumes. The water saturation in a reservoir is a function of the reservoir rock quality and the capillary forces present. Pore throat size distribution and rock quality strongly influence the amount of capillary-bounded water and mobile water in the reservoir rock. A good understanding and proper classification of rock types based on reservoir quality is essential for reservoir property population. Also, in absence of the core data, the practice of using single-well models and well logs to identify capillary pressure curves and hence water saturation distribution is not ideal for a vast heterogeneous reservoir with many wells. A case study is presented in which extensive core data, in particular RCA and SCAL results, are analyzed. These results are integrated with petrophysical interpretation to identify different classes of sand units based on the reservoir rock quality and amount of clay present. It is uniquely noted in this work that volume of clay, Vclay, was a better basis for rock classification in this reservoir. A numerical method is used to unify and integrate SCAL data acquired over a 1000-m section of the reservoir in more than 10 drilled wells. Parameterized equations are derived to populate initial water saturation in the static or dynamic model. The water saturations obtained from these parametric equations are subsequently validated with the well log saturations and vice versa. These results are further validated by history matching the drillstem test result, showing excellent results.

Abstract This paper illustrates the importance of classification and identification of rock types within integrated reservoir characterization studies. The goal is not to present a new classification scheme, but to draw attention to the benefits of a classification that provides the basis for populating a geo-cellular model with key attributes (porosity, permeability, saturation). Rock type, as derived from an integration of core examination, routine and special core analysis and wireline logs, and conditioned with well tests, facilitates geologically reasonable property prediction. The study concludes that a single classification scheme is impractical for all aspects of geological modeling. This work stems from a comprehensive reservoir description study of the Jurassic Arab C and D reservoirs of the Dukhan field. Core descriptions, routine core analysis, and visual examination of log data form the basis for recognition of an initial classification internally named ResFacs (Reservoir Facies). Because ResFacs originate from core, volume fractions and distribution are readily derivable from a cycle-based, sequence stratigraphic interpretation. Mineralogical and depositional trends of ResFacs form an initial conditioning parameter for models. This core-based classification is also used in all routine and special core analysis (SCAL) to segregate rocks of differing reservoir quality. It forms the common variable between all other classifications. SCAL data reveals reservoir quality trends that are not resolvable from core description and routine analyses alone. Most important were trends in fine-grained, muddy limestones and very coarse-grained lime grainstones. MICP data and saturation height modeling reveals a small volume of low porosity lime mudstones with such fine pore systems that they are unlikely to have been filled with hydrocarbons. At the other end of the spectrum, SCAL data and petrography reveal a class of coarse grainstones with point of contact cements that exhibit extremely high permeability. These data are used to modify the ResFac classification for use in calibration of well logs. Log-derived rock types, referred to as Petrophysical Reservoir Facies (PRFs) have been established to increase input data density for property distribution in geological models. As with many oilfields, historical SCAL and routine core analyses of variable quality are available. In order to make use of these data, samples were classified within the ResFac scheme. In addition, 100 representative samples were selected for further analysis (MICP, NMR, petrology, and porosity-permeability measurement at ambient and overburden conditions). This dataset provides a means of resolving pore systems by rock type and allows incorporation of historical data analyzed under variable laboratory conditions. The ResFac classification scheme is impractical for numerical modeling. Accordingly, ResFacs were consolidated based on texture, mineralogy, and rock type with unique saturation height functions. The final input into flow simulation models is termed Reservoir Rock Types (RRTs). These RRTs are used for property prediction, and calibration occurred with static data (e.g., initial water saturation from logs) and dynamic data (e.g., well test permeability-thickness and profiles from production logging tools). Rigorous rock description and comparison to measured static and dynamic data ensure that models based on RRTs describe fluid distribution and fluid flow capability.

ABSTRACT Mud logging gas detection and chromatography have been traditionally used as indicators of hydrocarbon occurrence and wellsite safety. However, the application of mud logging gas as a reliable reservoir characterization tool had previously been hindered by its semi-quantitative nature, noticeably the inability to get repeatable responses in all environments so that the analysis can be used as a trusted analytical tool, regardless of gas trap operating conditions and surface environments. A new gas extraction system, Constant Volume Gas Trap (CVGTTM), is now available at wellsite and has been successfully run worldwide. Equipped with several innovative features, CVGT not only improves mud gas extraction efficiency, but also reduces the effects of environmental and operation conditions on quantitative gas measurement. Coupled with high accuracy and a fast cycle gas chromatography system, CVGT gas ratio analysis provides a cost-effective approach to evaluate reservoir fluid types, contacts, and other critical information needed for subsequent fluid sampling, testing, and development programs. Several applications of gas ratio analysis are presented that complement other reservoir characterization tools and approaches. Vigorous data QC are enforced to reduce the effects of any non-reservoir fluid contributions. Most suitable ratio cutoffs are determined for the target reservoirs. These cutoffs are determined through a variety of factors, in particular the known reservoir fluid properties from offset wells in the area. C1/sum(C1~C5), and the combined use of gas wetness ratio (GWR) and light heavy ratio (LHR) have proved to be the most valuable out of all the gas ratios investigated. Together with total gas and gas chromatography, these ratios and ratio combinations are able to indicate the occurrence of reservoir zone, the types of fluid in it, and the fluid contacts. Fluid types defined from ratio analysis are correlated with LWD/wireline data, particularly the resistivity, cross-over of neutron and density, and pressure gradient analysis. This ultimately leads to better reservoir characterizations with regards to its vertical connectivity, compartment and caprock efficiency, etc. INTRODUCTION Accurate reservoir characterization in terms of accurate fluid type, contacts, and vertical evolution and compartmentalization at the early stage of well construction is vital for guiding subsequent fluid sampling, completion, well testing, and production planning and designing. It is also critical to identify the rock and fluid properties accurately in real time to maintain the well in an optimal trajectory for maximum productivity. Such endeavors are often not trivial, especially in producing reservoirs where complications arise due to altered gas/oil/water contacts from virgin status. Such alterations of contacts often result from combined effects of gas cap expansion, continuing production, and water injection.

Abstract Recent development of 3D seismic technology enables to visualize three-dimensional distributions of subsurface reservoir rock bodies. It is expected that linking this technology to sedimentological concept and methods such as depositional systems and sequence stratigraphy leads to realistic and efficient solutions in reservoir distribution analysis, since such genetic process information provides a guideline for better interpretation and evaluation. This study attempted to analyze 3D seismic geomorphology of submarine-fan turbidite reservoirs by integrating sedimentological methods and 3D seismic technique. As case study examples, total 40 stratigraphic horizons in four fields, where the major depositional system is submarine-fan turbidite system, were selected in active margin basins mainly around Japan. Detailed distribution analysis and sedimentological interpretation were conducted on 3D seismic data by displaying sediment bodies, using seismic facies, amplitude volume and various seismic attribute data to determine finer depositional elements of submarine fans. In the seismic facies mapping, software that categorized seismic trace shapes as an element of seismic facies was used for mapping seismic facies distributions. Subsequently, the shape of the displayed and interpreted submarine fans was categorized qualitatively, and the dimensions were measured quantitatively. In this study, four types of submarine-fan shape were identified (Type I, II, III and IV) as major morphology of active margin submarine fans. Type I represents a sandy radial fan type, containing distributary channels and depositional lobes. Type II represents an elongated muddy channel-levee type, which comprises elongated sandy channels and muddy levees. Type III represents a mixture of Type I and Type II, consisting of a leveed channel at the proximal part and a terminal fan at the distal part. Type IV represents a large mound type, which is composed of muddy sediments. These results are expected to be a useful tool for submarine-fan turbidite reservoir exploration and development in active margin basins. Introduction Recent development of 3D seismic technology enables to obtain realistic subsurface geologic data and to visualize three-dimensional distributions of geologic bodies using seismic attributes and 3D visualization techniques. Traditional subsurface analysis based on one-dimensional and two-dimensional data required estimation for areas that were not covered by data. In contrast, 3D seismic technology enables to obtain actual three-dimensional morphology, structure and distribution of geologic bodies without any estimation. From this aspect, the 3D seismic technology has been widely applied for recent hydrocarbon exploration and development projects, and provides strong impacts on reservoir distribution analysis, production management and reservoir characterization works. This paper focuses on sedimentological usage of 3D seismic technology, which can be applied for reservoir distribution analysis and reservoir characterization works. First, this paper reviews a historical background for the relationships between 3D seismic technology and sedimentology, introducing the development of the "seismic geomorphology 1 "concept. Subsequently, as an actual application example, this study selects submarine fan system, and presents the results of seismic geomorphological analysis for submarine-fan turbidite sandstone reservoir distributions with special reference to submarine-fan shape variations in a tectonically active area.

Abstract The High Density MC3D seismic survey, acquired by PGS in 2003 over the North Madura platform, is excellent data for quantitative interpretation of carbonate buildups. Detailed imaging of the growth histories of Oligocene-Miocene carbonate buildups provides insight into geometric parameters characteristic of platform initiation, development, and demise. Mound initiation occurs with development of small (<100 m to 500 m diameter), closely spaced, domal buildups, which become the nuclei for the formation of intermediate mounds (2 km to 3 km diameter). Nucleation mounds build concentrically to form intermediate mounds, which selectively coalesce into amalgamated platforms (>5 km diameter), become isolated platforms of varying size (<5 km diameter), or die off altogether. The high resolution and quality of the seismic data enable visualization and quantitative analysis of geometry, orientation, and spatial distribution of nucleation and intermediate mounds, suggesting models for development of mounds in platform, basinal, and channelized regions. Seismic Discontinuity time-slices datumed at the base of the carbonate section provide clear images of mound morphology at discrete growth steps in each of these regions. Other seismic attributes (e.g., isochron) can be exploited by innovative volume interpretation techniques for extracting mound features and calculating geometric attributes such as mound area, aspect ratio, orientation, etc. directly from the seismic data. The resulting data provide dimensional, spatial, and seismic facies characteristics of carbonate buildups for conditioning geologic models. Additional ties to well and outcrop data improve prediction of reservoir presence, quality, and distribution. Introduction This study utilizes the PGS HD-MC3D seismic survey (PGS, 2003) to examine the evolution of Burdigalian (early Miocene) age carbonate build ups on the North Madura platform in north central East Java Basin (Figure 1). In addition to visualizing the features of carbonate mounds in the seismic data, the aim of this study was to derive and compile a comprehensive database of quantitative dimensional and geometric data for various growth stages of Burdigalian mounds directly from 3D seismic data (Figure 2). This database improves the understanding of the evolution of carbonate mounds of this age and capabilities for predicting the size, shape, and distribution of Burdigalian mounds. It is also a resource for conditioning and populating geologic models in analogous areas where seismic data is limited. The HD-MC3D survey covers a portion of the 200+ km in length Oligo-miocene North Madura carbonate platform (Figure 1B). It is a high resolution survey with spectacular imaging of the Tertiary carbonate section, as well as clastic intervals and structural features (Figure 3). Examples of the details of the early Miocene section imaged in the survey are shown in Figure 1 in a discontinuity time slice (Figure 1D) and a shaded relief map of the time surface for the Burdigalian interval (Figure 1E).

Abstract Human error is cited as a contributing factor in the majority (up to 80%) of industrial accidents and incidents. The Human Factors Assessment and Classification System (HFACS) was adapted for use in the Oil & Gas (O&G) industry to provide a common framework to systematically classify accident contributing factors. HFACS originates from the aviation industry and is based on Reason's model of latent and active failures, the "Swiss cheese" model. The framework defines the "holes in the cheese" with four main categories of conditions/failures; Acts, Preconditions, Supervision, and Organizational Influences. Each category contains a set of failure codes, known as nanocodes. The O&G HFACS can be applied to accidents on fixed or mobile installations for production or drilling. Integrated Operations (IO) or e-fields have introduced new ways of working and allows for the formation of virtual organizations. O&G HFACS can be used to balance the Man-Technology-Organization (MTO) development in this context. Nanocodes from the US Department of Defence and the US Naval Safety Center were merged and adapted to form the O&G HFACS. The merged framework was reviewed and resulted in 23 changed, 61 removed, 18 added, and 144 unchanged nanocodes, leaving O&G HFACS with 185 nanocodes. Two important new aspects were the use of personnel with different cultural background and personnel's understanding of the language used for communication and documentation/procedures. The O&G HFACS was applied for validation purposes to four Norwegian offshore accidents that occurred during 2007. The framework was suitable for these accidents and revealed that latent failures on the organizational level were most prevalent, in particular oversight and procedures. O&G HFACS provides a common framework for comparison of accidents and incidents on many levels, e.g. within the industry, a company or installation. The framework can be useful to systemize accident information retrieved through an MTO approach. 1. Introduction There is no unified definition of ‘human error’ in existing literature. Human error can broadly be defined as " …all those occasions in which a planned sequence of mental or physical activities fails to achieve its intended outcome, and when these failures cannot be attributed to the intervention of some change agency "[1]. This definition does not separate between slips or lapses and mistakes, but generically defines error. Human Factors (HF) can be defined as " the scientific discipline concerned with the understanding of interactions among human and other elements of a system, and the profession that applies theory, principles, data and methods to design in order to optimize human well-being and overall system performance "[2]. In aviation are typically 60–80 percent of all accidents attributed to human error [3] and studies in offshore and maritime industries show that 80 percent of accidents and incidents involve human error [4]. The US coast guard refers to the human element as a causal factor in 80–90 percent of all mishaps [5]. However, the operator represents a convenient stopping point in an event-chain model of accidents [6] and hence, these numbers may be biased. Leveson [6] lists four reasons for such operator error statistics: only operator errors that negatively affect safety are reported, unrealistic expectations that the operator can overcome any emergency, operators may have to intervene unforeseen situations at the limits of the system and hindsight often allows us to identify better decisions in retrospect.

This reference is for an abstract only. A full paper was not submitted for this conference. Abstract The Tertiary slope deposits of the Australian NW shelf show a complex imbrications of apparently erosional surfaces. Observed in 3D, these surfaces appear as essentially made up of coalescent craters. This morphology indicates that they do not correspond to canyons or channels as could be suggested by cross-sectional views only. Detail seismic correlation between the infill of the craters and the surrounding areas shows that the craters actually formed below sedimentary cover, in other terms correspond to sediment dissolution at depth and not erosion at the seafloor. Individual craters typically measure about 1 to 2 km in diameter and are 100 to 300 m deep. They can also be strongly elongated and at some levels coalesce to make very irregular surfaces over several hundreds of km2. Craters affect most of the Palaeocene and Eocene of the studied area, i.e. a thickness of about 1 km. The lithology of the interval is dominated by carbonates and claystones. The stratigraphic relationships with the adjacent shelf indicates that the area was already in the deep domain at the time of deposition. This rules out a formation process by continental karst for the craters. At the same time, the conical geometry is more reminiscent of pockmarks or conical injections than of collapsed karsts. Recently published work in the Gulf of Guinea has evidenced seafloor craters associated with the progressive dissolution of gas hydrates, with sizes comparable to what is observed in the NW shelf area. The complex seismic morphology observed in the Tertiary of the studied area is therefore tentatively interpreted to reflect successive episodes of growth and dissolution / dissociation of km-scale hydrate bodies in shallow subsurface. The episodes of dissolution may be related to the pressure fluctuations associated with relative sea-level changes. Whatever the exact dissolution mechanism, this represents a significant departure from classical "erosional" models in deep water, and should be considered in presence of highly irregular reflectors to avoid erroneous conclusions about the reservoir potential of affected series for instance.