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Weighting agents or heavyweight additives are used to increase slurry density for control of highly pressured wells. Weighting agents are normally required at densities greater than 17 lbm/gal where dispersants or silica is no longer effective. This is the most commonly used weighting agent. Hematite is a brick-red, naturally occurring mineral with a dull metallic luster. It contains approximately 70% iron.
Abstract The Ivar Aasen (IA) oilfield is located on the Gudrun Terrace on the eastern flank of the Viking Graben in the Norwegian North Sea. The field was discovered in 2008. The reservoir is located within a sedimentary sequence of Mid-Jurassic to Late-Triassic age, which consists of shallow marine to fluvial, alluvial, floodplain and lacustrine deposits overlying a regionally extensive, fractured calcrete interval. The sequence exhibits a complex mineral composition and is heterogeneous at a scale below that of a logging sensor. Shale layers, re-deposited shale and what was first believed to be redeposited calcrete fragments present in various forms throughout the sequence. Looking more in depth to XRD and XRF data and contrasting Fe concentration in the dolomite, it is also possible to explain some of the carbonate deposits through other processes. Extensive data acquisition in the form of advanced wireline logs and coring with analysis performed in “geopilot” wells before production start, enabled a novel thin bed formation evaluation technique based on the modified Thomas-Stieber method (Johansen et al. 2018). The method increased the in-place oil volumes within the Triassic reservoir zone internally named Skagerrak 2. This led to several improvements and a modified drainage strategy of Ivar Aasen. Several good producers were placed in the complex net of the Skagerrak 2 Formation. Results from these producers have encouraged development of an even more marginal and complex net, deeper into the Triassic sedimentary sequence. Therefore, another “geopilot” was drilled into the deeper Triassic sediments, internally named as the Alluvial Fan. This zone exhibits conglomerate clasts in a matrix varying between clay, silt, feldspars, and very fine to very coarse sand fractions, grading towards gravel. Previously, this zone was considered to be mostly non-net. Applying the same interpretation method as for Skagerrak 2, the Alluvial Fan promised economic hydrocarbon volumes. The latest geopilot proved producible hydrocarbons, and subsequently a producer was also successfully placed in this part of the reservoir. Production data and history matching from the beginning of production have for a long while established the previous increase of IA Triassic oil volumes published in 2018. Advanced studies of mineralogy and spectroscopy (Johansen et al. 2019) have indicated that a significant amount of the previously interpreted dolomite, could be reinterpreted as ferroan dolomite. The latter is a heavier mineral that increases the matrix density, hence also the total porosity. The additional findings described provided another necessary first-order correction to further enhance the evergreen geomodel. This paper describes this methodology which resulted in improved petrophysics and reservoir properties of the Alluvial Fan, yet again demonstrating the value of advanced wireline logs and detailed analysis that in total impacts the IA reserve volumes in a significant manner. Repeated success with the applied spectroscopy data and the thin bed methodology used today (Johansen et al. 2018), has resulted in even the deeper Braid Plain Formation becoming of economic interest. It is expected to lie within the oil zone in an upthrow block in the northern part of the IA field and could be developed into the next target.
Abstract Although a relationship between gamma ray log response and shale volume had been recognized since the introduction of gamma ray logging in the late 1930s and early 1940s, the formula for gamma ray index, and the equating of gamma ray index to shale volume apparently appeared in the late 1960s. Contemporaneously there appeared three similar, alternative, non-linear relationships in 1969, 1970, and 1971. These functions were based upon observations and empirical graphical functions. Subsequently, these graphical functions were fit using very dissimilar-looking formulas. Only the 1969 data set was published in support of the graphical functions. No attempt to link these functions with a single formula was ever made, and only vague verbal explanations have been offered for the non-linear functions. Further, the 1969 publication was in Russian, partly mistranslated, and the mistranslation never corrected. Consequently, two of the resulting formulas are misapplied. In this article I review the four standard non-linear functions (i.e., Larionov’s two, Stieber’s, Clavier’s), examine their similarities, and show that a single function would serve the same purpose as all four, thereby eliminating a source of confusion for formation evaluators. When these shale (or clay) volume versus gamma ray index transforms are inverted to functions of gamma ray index versus shale (or clay) fractional volume a remark-able property is revealed: the increment of radioactivity per unit shale volume decreases with increases in fractional shale volume. In other words, if one unit of shale per unit volume produces a gamma ray intensity of 10 API units we would think it strange if 10 units of shale per unit volume produced only, say, 60 API units of gamma radiation (instead of 100). Yet, this is the message contained in these functions. The cause for this phenomenon has been speculated upon, but only briefly and not often. To remedy this lack of speculation, I propose a physical model and give it mathematical form. This model is in-tended as a challenge to theoretical-minded petrophysicists to falsify it, make it better, or propose an alternative and more realistic model. I also provide (in Appendix C) a digital listing of all the published graphical data in the literature that support the introduction of the non-linear shale (and clay) fractional volume - gamma ray index transforms.
Craddock, Paul (Schlumberger-Doll Research Center) | Srivastava, Prakhar (Schlumberger-Doll Research Center) | Datir, Harish (Schlumberger) | Rose, David (Schlumberger) | Zhou, Tong (Schlumberger) | Mosse, Laurent (Schlumberger) | Venkataramanan, Lalitha (Schlumberger)
Abstract This paper describes an innovative machine learning application, based on variational autoencoder frameworks, to quantify the concentrations and associated uncertainties of common minerals in sedimentary formations using the measurement of atomic element concentrations from geochemical spectroscopy logs as inputs. The algorithm comprises an input(s), encoder, decoder, output(s), and a novel cost function to optimize the model coefficients during training. The input to the algorithm is a set of dry-weight concentrations of atomic elements with their associated uncertainty. The first output is a set of dry-weight fractions of fourteen minerals, and the second output is a set of reconstructed dry-weight concentrations of the original elements. Both sets of outputs include estimates of uncertainty on their predictions. The encoder and decoder are multilayer feed-forward artificial neural networks (ANN), with their coefficients (weights) optimized during calibration (training). The cost function simultaneously minimizes error (the accuracy metric) and variance (the precision or robustness metric) on the mineral and reconstructed elemental outputs. Training of the weights is done using a set of several-thousand core samples with independent, high-fidelity elemental and mineral (quartz, potassium-feldspar, plagioclase-feldspar, illite, smectite, kaolinite, chlorite, mica, calcite, dolomite, ankerite, siderite, pyrite, and anhydrite) data. The algorithm provides notable advantages over existing methods to estimate formation lithology or mineralogy relying on simple linear, empirical, or nearest-neighbor functions. The ANN numerically capture the multi-dimensional and nonlinear geochemical relationship (mapping) between elements and minerals that is insufficiently described by prior methods. Training is iterative via backpropagation and samples from Gaussian distributions on each of the elemental inputs, rather than single values, for every sample at each iteration (epoch). These Gaussian distributions are chosen to specifically represent the unique statistical uncertainty of the dry-weight elements in the logging measurements. Sampling from Gaussian distributions during training reduces the potential for overfitting, provides robustness for log interpretations, and further enables a calibrated estimate of uncertainty on the mineral and reconstructed elemental outputs, all of which are lacking in prior methods. The framework of the algorithm is purposefully generalizable that it can be adapted across geochemical spectroscopy tools. The algorithm reasonably approximates a ‘global-average’ model that requires neither different calibrations nor expert parameterization or intervention for interpreting common oilfield sedimentary formations, although the framework is again purposefully generalizable so it can be optimized for local environments where desirable. The paper showcases field application of the method for estimating mineral type and abundance in oilfield formations from wellbore logging measurements.
Abstract Reliable quantification of wettability is critical in assessment of fluid distribution, capillary pressure, relative permeability, and flow properties of fluids in reservoirs. Wettability of reservoirs can be affected by chemical composition of rock-fluid system, salinity, and reservoir temperature. Experimental assessment of wettability under reservoir conditions, while gaining control on the aforementioned parameters, may be tedious and challenging. Several published researches have used experimental studies to focus on determining the impact of individual factors on wettability of rock. However, studies on the combined effects of these factors are limited, although critical, for better understanding of wettability of hydrocarbon reservoirs. In this paper we introduce a workflow for assessment of wettability of rocks at reservoir condition using molecular dynamics (MD) simulations. The outcomes include (i) quantifying the wettability of pure minerals, (ii) quantifying the impact of reservoir temperature on wettability of pure mineral. The inputs to the simulation include molecules of pure minerals (quartz, calcite, albite) packed in a cubical simulation box. The molecules are condensed to form a flat surface. Subsequently, water and oil (hexane) molecules are placed on the surface of the mineral. We then perform simulations with constant number of particles, temperature and volume (NVT) on the system till equilibrium is reached. At equilibrium, the contact angle formed by the water droplet is measured. Contact angle is simulated for temperature conditions in the range of 300 to 380 K. The results showed that the contact angle between water-mineral for quartz, calcite, and albite at room temperature (300 K) ranges from 30º to 45º, indicating that the surface of these minerals is hydrophilic, with different degrees of hydrophilicity. This information is essential for reliable fluid flow simulations, which are often overlooked in conventional approaches. We also found that the temperature has a measurable impact on the contact angles formed by water droplet. We found that increase in temperature from 300 to 380 K decreases the contact angles by approximately 30% on quartz surfaces, 20% on albite surfaces, and 24% on calcite surfaces. The results for the hexane-mineral system show that the hexane behaved similarly in the three minerals surface. A thin film of hexane is formed at the surface corresponding to a contact angle of 0º. The method introduced in this paper has application for reliable evaluation of wettability at any reservoir of interest by knowing the molecular structure of clay and non-clay minerals as well as fluid content. Moreover, the challenges of wettability determination under high temperature and pressure conditions can also be efficiently addressed by using molecular dynamics simulations.
A clay type marked by platelet like deposits in the authogenic form. Usually not water sensitive but may have occasional loose attachment to the host grain. The layers of a kaolinite mineral are not expandable. The cation exchange capacity and specific surface are in the low range compared to most other common clay minerals. The cation exchange capacity of kaolinite is very pH dependent.
Abstract Natural gas is the noble fuel of 21st century. Consumption increased nearly 30% in last decade. Exploitation of conventional, unconventional, and contaminated gas resources are in focus to meet the demand. There are number of giant gas fields discovered worldwide and some of them with higher degree of contaminants viz. CO2, H2S and Hg. Additionally, they have operating challenges of high pressure and temperature. It becomes more complex when discovery is in offshore environment. This study presents the development and production, separation, transportation and identification & evaluation of storage sites and sequestration and MMV plan of a giant carbonate gas field in offshore Malaysia. Geological, Geophysical and petrophysical data used to describe the reservoir architecture, property distribution and spatial variation in more than 1000m thick gas bearing formation. Laboratory studies carried out to generate the rock and fluid representative SCAL (G-W), EOS and Supercritical CO2-brine relative permeability, geomechanics and geochemical data for recovery and storage estimates in simulation model and evaluating the post storage scenario. These data are critical in hydrocarbon gas prediction and firming up the number of development wells and in the simulation of CO2 storage depleted carbonate gas field. Important is to understand the mechanism in the target field for storage capacity, types of storage- structural and stratigraphic trapping, solubility trapping, residual trapping and mineral trapping. Study covers methodologies developed for minimization of hydrocarbon loss during contaminants separation and utilization of CO2 in usable products. Uncertainty and risk analysis have been carried out to have range of solution for production prediction and CO2 storage. Coupled Simulation studies predict the production plateau rate and 5 Tscf recovery separated contaminants profile and volume > one Tscf in order to have suitable geological structure for storage safely forever. Major uncertainties in the dynamic and coupled geomechanical-geochemical dynamic model has been captured and P90, P50, P10 forecast and storage rates and volumes have been calculated. Results includes advance methodologies of separation of hydrocarbon gas and CO2 like membrane and cryogenics for bulk separation of CO2 from raw gas and its transportation in liquid and supercritical form for storage. Study estimates components of sequestration mechanism, effect of heterogeneity on transport in porous media and height of stored CO2 in depleted reservoir and migration of plume vertically and horizontally. Generation of chemical product using separated CO2 for industrial use is highlighted.
Kasim, Fadzlin Hasani (PETRONAS Research Sdn Bhd) | Kantaatmadja, Budi Priyatna (PETRONAS Research Sdn Bhd) | Wan M Zainudin, Wan Nur (PETRONAS Research Sdn Bhd) | Ali, Amita (PETRONAS Research Sdn Bhd) | Ismail, Hasnol Hady (PETRONAS Research Sdn Bhd) | Ahmed Siddiqui, Numair (Universiti Teknologi PETRONAS)
Abstract Predicting the spatial distribution of rock properties is the key to a successful reservoir evaluation for hydrocarbon potential. However, a reservoir with a complex environmental setting (e.g. shallow marine) becomes more challenging to be characterized due to variations of clay, grain size, compaction, cementation, and other diagenetic effects. The assumption of increasing permeability value with an increase of porosity may not be always the case in such an environment. This study aims to investigate factors controlling the porosity and permeability relationships at Lower J Reservoir of J20, J25, and J30, Malay Basin. Porosity permeability values from routine core analysis were plotted accordingly in four different sets which are: lithofacies based, stratigraphic members based, quartz volume-based, and grain-sized based, to investigate the trend in relating porosity and permeability distribution. Based on petrographical studies, the effect of grain sorting, mineral type, and diagenetic event on reservoir properties was investigated and characterized. The clay type and its morphology were analyzed using X-ray Diffractometer (XRD) and Spectral electron microscopy. Results from porosity and permeability cross-plot show that lithofacies type play a significant control on reservoir quality. It shows that most of the S1 and S2 located at top of the plot while lower grade lithofacies of S41, S42, and S43 distributed at the middle and lower zone of the plot. However, there are certain points of best and lower quality lithofacies not located in the theoretical area. The detailed analysis of petrographic studies shows that the diagenetic effect of cementation and clay coating destroys porosity while mineral dissolution improved porosity. A porosity permeability plot based on stratigraphic members showed that J20 points located at the top indicating less compaction effect to reservoir properties. J25 and J30 points were observed randomly distributed located at the middle and bottom zone suggesting that compaction has less effect on both J25 and J30 sands. Lithofacies description that was done by visual analysis through cores only may not correlate-able with rock properties. This is possibly due to the diagenetic effect which controls porosity and permeability cannot visually be seen at the core. By incorporating petrographical analysis results, the relationship between porosity, permeability, and lithofacies can be further improved for better reservoir characterization. The study might change the conventional concept that lower quality lithofacies does not have economic hydrocarbon potential and unlock more hydrocarbon-bearing reserves especially in these types of environmental settings.