We introduce a new quantitative approach to improve the petrophysical evaluation of thinly bedded sand-shale sequences that have undergone extensive diagenesis. Formations under analysis consist of carbonate-rich clastic sediments, with pore system heavily reworked by calcite and authigenic clay cementation, giving rise to rocks with high spatial heterogeneity, low porosity, and low permeability. Porosity varies from 2 to 20% and permeability varies from less than 0.001 mD to 200 mD. Diagenesis and thin laminations originate complex magnetic resonance (NMR) T2 distributions exhibiting multimodal distributions. Furthermore, reservoir units produce highly viscous oil, which imposes additional challenges to formation evaluation. Petrophysical evaluation of thinly bedded formations requires accurate estimation of laminar and dispersed shale concentration. We combined Thomas-Stieber’s method, OBMI, and Rt-Scanner measurements to calculate laminar shale concentration. Results indicate that hydrocarbon reserves can be overestimated in the presence of high-resistivity streaks and graded beds, which give rise to electrical anisotropy. To account for electrical anisotropy effects on petrophysical estimations, we classified reservoir rocks based on the cause of electrical anisotropy. Thereafter different interpretation methods were implemented to estimate petrophysical properties for each rock class. We also appraised the advantages and limitations of the high-resolution method for evaluating thinly bedded formations with respect to other petrophysical interpretation methods. Numerical simulations were performed on populated earth-model properties after detecting bed boundaries from resistivity or core images. Earth-model properties were iteratively refined until field and numerically simulated logs reached an acceptable agreement. Results from the high-resolution method remained petrophysically consistent when beds were thicker than 0.25 ft. Numerical simulations of NMR T2 distributions were also performed to reproduce averaging effects of NMR responses in thinly bedded formations, which enabled us to improve the assessment of pore-size distributions, in-situ fluid type, and saturation. Permeability of sand units was estimated via Timur-Coates’ equation by removing the effect of laminar shale on porosity and bulk irreducible volume water. Shoulder-bed corrected logs were input to the calculations. Petrophysical properties obtained with the developed interpretation method honor all the available measurements including conventional well logs, NMR, resistivity images, multi-component induction, and core measurements. The developed interpretation method was successfully tested across four hydrocarbon-saturated intervals selected from multiple wells penetrating a deep turbidite system. Permeability values obtained with the new interpretation method improved the correlation with core measurements by 16% as compared to permeability calculations performed with conventional methods. In addition, on average the method yielded a 62% increase in hydrocarbon pore-thickness when compared to conventional petrophysical analysis. / text

Masters of Science / This study is focused on the Coal Bed Methane resources of Botswana with specific reference to the Central Kalahari basin where prospect license blocks forming the focus of this study are located. The aim of this study is to evaluate the fracture network in the coal seams and the fracture systems in the surrounding coal bearing sedimentary sequences and their contribution to dynamic flow. Coal bed methane sources are dual-porosity media documented on the natural fracture network, seen as micropores (matrix/natural fractures) and macropores (cleat). The coals of this region belong to the Ecca Group’s Morupule Fm (Permian) (70 m), focus of this study and have been preserved in the extensive Karoo basin within the Southern Africa region. Fractures can easily be identified in Acoustic Televiewer logs (ATV) and their orientation and structural character interpreted by rose plots, tadpoles and stick dip plots. In-situ stress fields have been determined from breakout structural evaluation and maintains a general E-W dip direction and N-S strike, thus most fractures are orientated optimally with inferred in-situ stress and enhancing flow potential in pore systems. A qualitative (MID plots & M-N cross-plots) and quantitative description of the fracture system is fundamental to the petrophysical evaluation, and involves the estimation of fracture parameters (fracture porosity, resistivity fracture index and both horizontal and vertical fracture indices).

>Magister Scientiae - MSc / The goal of this study is to enhance the evaluation of subsurface reservoirs by improving the prediction of petrophysical parameters through the integration of wireline logs and core measurements. Formation evaluations of 13A and 14A sequences in the Bredasdorp Basin, offshore South Africa have been performed. Five wells in the central area of the basin have been selected for this study. Four different lithofacies (A, B, C, D) were identified, in the two cored wells, and used to predict the lithofacies from wireline logs in uncored intervals and wells. A method based on artificial neural network was used for this prediction. Facies A and B were recognized as reservoir rocks and 13 reservoir zones were identified and successfully evaluated in a detailed petrophysical model. The final shale volume was considered to be the minimum among five different methods applied in this study at any point along the well log. The porosity model was taken from the density model. A value of 2.66 g/cm3 was obtained from core measurements as the field average grain density, whereas the value of the fluid density of 0.79 g/cm3 was obtained from core porosity and bulk density cross-plot. In a water saturation model; an average water resistivity of 0.135 Ohm-m was estimated from SP method. The calculated water saturation models were calibrated with core measurements, and the Indonesia model best matched with the water saturation from conventional core analysis. Six hydraulic flow units were recognized in the studied reservoirs, and were used for permeability predictions. The permeability predicted from hydraulic flow units were found more reliable than the permeability calculated from porosity-permeability relationship. The net pay was identified for each reservoir by applying cut-offs on permeability 0.1 mD, porosity 7%, shale volume 0.35, and water saturation 0.60. The gross thickness of the reservoirs ranges from 4.83m to 41.07m and net pay intervals from 1.21m to 29.59m.

Dans les puits de production d’eau, de pétrole, de gaz et de chaleur géothermique, ou dans les puits d’accès à un stockage d’hydrocarbures, il est précieux de connaître la perméabilité de la formation ou de sa couverture en fonction de la profondeur, soit pour améliorer le modèle de réservoir, soit pour choisir les zones dans lesquelles procéder à des opérations spéciales.On propose une technique qui consiste à balayer la hauteur du découvert par une interface entre deux liquides de viscosités très contrastées. Le débit total qui pénètre la formation à chaque instant est ainsi une fonction de la position de l’interface et de l’historique des pressions dans le puits. On doit alors résoudre un problème inverse : rechercher la perméabilité fonction de la profondeur à partir de l’historique des débits dans le temps. Dans la pratique, le puits est équipé d’un tube central. Le balayage est effectué par injection d’un liquide à pression d’entrée constante dans le tube central et soutirage d’un autre liquide par l’espace annulaire. On mesure les débits d’injection et de soutirage dont la différence est le débit qui entre dans la formation.Pour valider et améliorer cette technique, on a d’abord utilisé une maquette simulant un découvert multi-couches disponible au LMS. On a exploité aussi des essais en place réalisés dans la couverture peu perméable d’un stockage souterrain de gaz. Dans ces essais, un liquide visqueux placé dans le découvert était déplacé par un liquide moins visqueux (méthode dite « opening »). Les couches plus perméables étaient correctement identifiées (Manivannan et al. 2017), mais une estimation quantitative était un défi en raison des phénomènes transitoires qui affectent le voisinage immédiat des puits. De plus, le rayon investigué dans le massif était petit.La thèse a relevé ces défis en proposant un essai légèrement différent et une nouvelle technique d’interprétation. Les essais avec une maquette modifiée ont montré la supériorité d’une méthode « closing » dans laquelle le puits est d’abord rempli du liquide le moins visqueux. On ménage une période de stabilisation avant l’injection du liquide visqueux pour réduire les effets transitoires ; elle permet aussi d’estimer la perméabilité moyenne et l’influence de la zone endommagée à la paroi (le « skin »).Puis on conduit l’essai proprement dit. L’historique des débits mesurés en tête de puits constitue le profil d’injection dont on déduit le profil de perméabilité.. Cette estimation suppose un écoulement monophasique dans chaque couche et la même « skin » pour toute la formation. Les incertitudes principales portent sur les pressions de formation et les variations possibles du « skin ». Elles sont estimées au moyen d’un calcul analytique. On a vérifié sur la maquette que les profils de perméabilité estimés présentent une bonne concordance avec les perméabilités mesurées avant les essais.On a réalisé un essai sur un sondage de 1750 m de long atteignant une couche de sel dont on a correctement estimé la perméabilité moyenne pendant la période de stabilisation. Toutefois elle était si faible (4.0E-21 m²) que l’utilisation de deux fluides n’a pas permis de faire une différence entre les diverses parties du puits. / In wells producing water, oil, gas or geothermal energy, or in access wells to hydrocarbon storage, it is critical to evaluate the permeability of the formation as a function of depth, to improve the reservoir model, and also to identify the zones where additional investigation or special completions are especially useful.A new technique is proposed, consisting of scanning the open hole (uncased section of the wellbore) with an interface between two fluids with a large viscosity contrast. The injection rate into the formation depends on interface location and well pressure history. An inverse problem should be solved: estimate permeability as a function of depth from the evolution of flow rates with time. The wells are usually equipped with a central tube. The scanning is done by injecting a liquid in the central tube at constant wellhead pressure. Injection and withdrawal rates are measured at the wellhead; the difference between these two rates is the formation injection rate.To validate and improve this technique, we used a laboratory model mimicking a multi-layer formation, already available at LMS. We also made use of in-situ tests performed on an ultra-low permeable cap rock above an underground gas storage reservoir. In these tests, a viscous fluid contained in the open hole was displaced by a less-viscous fluid (a method called opening WTLog). The more permeable layers were correctly identified (Manivannan et al. 2017), but a quantitative estimation was challenging due to transient phenomena in the vicinity of the wellbore (near-wellbore zone). In addition, the investigation radius was small.These challenges are addressed by proposing a slightly modified test procedure and a new interpretation workflow. Laboratory tests with a modified test setup showed the advantages of the ‘closing’ method in which the well is filled with a less-viscous fluid at the start of the test. We also added a stabilization period before the injection of viscous fluid to minimize the transient effects; this period is also used to estimate the average permeability of the open hole and the effect of near-wellbore damage (skin).Then the test proper is performed (closing WTLog). The injection profile of the less-viscous fluid is computed from the wellhead flow rate history. A permeability profile is estimated from the injection profile. The permeability estimation considers a monophasic flow in each layer and the same skin value for all the formation layers. Major uncertainties in the permeability estimates are caused by formation pressures and heterogeneities in skin values; they are estimated using an analytical formula. We have verified on the laboratory setup that the estimated permeability profiles are well correlated to the permeabilities measured before the tests.An attempt was made to perform a WTLog in a 1750-m long wellbore opening in a salt formation. The first phase was successful and the average permeability was correctly assessed. However, this permeability was so small (4.0E-21 m² or 4 nD) that the gauges and the flowmeters were not accurate enough to allow a clear distinction between the permeabilities of the various parts of the open hole.