Résumé -Identification de fluides de réservoir par le rapport V p /V s -Le temps de propagation des ondes sismiques de compression est largement utilisé pour la détermination de la porosité. En se servant à la fois des ondes sismiques transversales et des ondes de compression, il est possible de discriminer les propriétés mécaniques des roches. L'utilisation du rapport de vitesses des ondes sismiques de compression et transversales, V p /V s , permet de définir une méthode pour identifier la nature des fluides saturant les pores de la roche. Le rapport V p /V s varie selon le fluide (eau, huile et gaz) présent dans les pores de la roche. Des exemples tirés des études de champs montrent comment la représentation du rapport V p /V s sous forme graphique permet d'identifier la nature des fluides saturant les roches de réservoir. Abstract

Reservoir evaluation is one of the critical tasks of any reservoir exploration and field development plan. Water saturation calculated from open-hole resistivity measurements is a primary input to hydrocarbon reserves evaluation. Archie's equation is the water saturation model for the determination of water saturation. Application of Archie equation in carbonate reservoir is not easy due to high dependency of its parameters on carbonate characteristics. Determination techniques of Archie's parameters are relatively well known and validated for sandstone reservoirs, while carbonates are heterogeneous and a correct estimation of Archie' parameter is important in their evaluation. In the case of carbonate rocks, there are considerable variations in texture and pore type, so, Archie's parameters become more sensitive to pores pattern distribution, lithofacies properties and wettability. Uncertainty in Archie's parameters will lead to non-acceptable errors in the water saturation values. Uncertainty analysis has shown that in calculating water saturation and initial oil in place, the Archie's parameters (a, m, n) have the largest influence and R t and R w are the least important. The main objective of this study was to measure Archie's parameters on 29 natural carbonate core plugs at reservoir conditions, using live oil, these core samples were taken from three wells. For this purpose, three techniques were implemented to determine Archie's parameters; conventional technique, core Archie's parameters estimate technique and three-dimensional technique. Water saturation profiles were generated using the different Archie parameters determined by the three techniques. These profiles have shown a significant difference in water saturation values and such difference could be mainly attributed to the uncertainty level for the calculated Archie parameters. These results highlight the importance of having accurate core analysis's measurements performed on core samples that yield representative a, m and n values that highly influence the water saturation values.

Analysis of heterogeneous gas sand reservoirs is one of the most difficult problems. These reservoirs usually produce from multiple layers with different permeability and complex formation, which is often enhanced by natural fracturing. Therefore, using new well logging techniques like NMR or a combination of NMR and conventional openhole logs, as well as developing new interpretation methodologies are essential for improved reservoir characterization. Nuclear magnetic resonance (NMR) logs differ from conventional neutron, density, sonic and resistivity logs because the NMR measurements provide mainly lithology independent detailed porosity and offer a good evaluation of the hydrocarbon potential. NMR logs can also be used to determine formation permeability and capillary pressure. In heterogeneous reservoirs classical methods face problems in determining accurately the relevant petrophysical parameters. Applications of artificial intelligence have recently made this challenge a possible practice. This paper presents a successful application of Neural Network (NN) to predict porosity and permeability of gas sand reservoirs using NMR T2 (transverse relaxation time) and conventional open hole logs data. The developed NN models use the NMR T2 pin values, and density and resistivity logs to predict porosity, and permeability for two test wells. The NN trained models displayed good correlation with core porosity and permeability values, and with the NMR derived porosity and permeability in the test wells. Introduction Porosity logs measurements require environmental corrections and are influenced by lithology and formation fluids. The porosity derived is the total porosity, which consists of producible fluids, capillary bound water and clay-bound water. However, NMR provides lithology independent porosity and includes only producible fluids and capillary bound water. Permeability is a measure of fluid rock conductivity. To be permeable, a rock must have interconnected porosity. Greater porosity usually corresponds to greater permeability; however, this is not always the case. Formation permeability is influenced by pore size, shape and continuity, as well as the amount of porosity. Permeability can be determined from resistivity gradients, permeability models based on porosity, f, and irreducible water saturation (Swi), formation tester (FT) and nuclear magnetic resonance (NMR). Perhaps, the most important feature of NMR logging is the ability to record a real-time permeability log. The potential benefits of NMR to oil companies are enormous. Log permeability measurements enable production rates prediction and allow optimization of production completion and programs stimulation while decreasing the cost of coring and testing wells especially in heterogeneous tight reservoirs where there is considerable permeability anisotropy.

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There are many reasons for low resistivity pay zones phenomenon. It is of crucial importance to know the origin of this phenomenon. The problem with these zones is that the resistivity data interpretation indicates high water saturation, but oil or even dry oil will be produced. This paper discuss the different reasons sandstone reservoir can have low resistivity. Clean oil bearing sandstone has high resistivity, but when this rock contains shale, or heavy minerals such as pyrite, the resistivity can become low. This paper deals with the case of shaly sand formation as a low resistivity pay zone. Different shaly sand models will be applied. It has been found that the modified total shale sand model gives good results. Field example is presented to show the results of different models.