This paper presents a logical approach to ensure successful nuclear magnetic resonance (NMR) logging for fluid-characterization purposes. Numerous examples are shown in a three-stage process consisting ofplanning,processing and interpretation, andvalidation and integration. First, modeling is performed to assess the NMR contrast, using any available information concerning anticipated fluid types. Knowledge of downhole conditions also allows the estimation of the NMR signal-to-noise ratio (SNR) from which the sensitivity and statistical error can be evaluated. The outcome of the planning process is a suite of NMR pulse sequences that optimizes resolution of the different fluids and minimizes error with the shortest possible acquisition time. Interpreting fluid-characterization NMR logs is relatively straightforward when the fluids have large NMR contrast and obey the standard correlations. However, dissolved gas, wettability variations, internal field gradients, and restricted diffusion can cause deviations from model behavior and have significant effects on NMR relaxation data. These effects need to be recognized and accounted for. To gain insights into the NMR-based fluid evaluation process, we have developed a model-independent technique that gives various sets of D-T1-T2 maps. The maps are analogous to the crossplots commonly used in log interpretation practices and are indispensable in the interpretation of the data. We also explain quantitative interpretation techniques from D-T2 maps. Integrating NMR fluid-characterization results with other information and openhole logs constitutes the final step. As with any technique, results need to be crosschecked with other log data for consistency. The answer gives a water saturation that can be verified with other tools and techniques such as the dielectric log, resistivity logs, and the density magnetic resonance technique method. Introduction Current methods to analyze fluids using suites of NMR measurements employ model-based inversions. Two examples of the forward-modeling approach are the MACNMR1 and Magnetic Resonance Fluid (MRF) characterization methods.2 The MRF technique is based on physical laws that are calibrated empirically to account for the downhole fluid NMR responses. By using realistic fluid models, MRF aims to minimize the number of adjustable parameters to be compatible with the information content of typical NMR log data. Since the model parameters are by design related to the individual fluid volumes and properties, determination of the parameter values (i.e., data-fitting) leads directly to estimates of the fluids petrophysical quantities. Any forward-model approach relies on the validity of the fluid models employed. In "non-ideal" situations where the fluid NMR response deviates from the model behavior (such as internal gradient, oil-wet rocks, restricted diffusion etc.), these techniques may lead to erroneous answers. In some circumstances, "non-ideal" responses may be identified by a poor fit-quality of the echo data, in which case the fluid models can be adjusted by modifying the appropriate model parameters. However, it may not be obvious which element of the fluid model should be modified and what modification is needed to get the desired answer. The maximum entropy principle (MEP) method is a model-independent inversion that provides a simple graphical representation of NMR data for fluid analysis in all environments. The graphical representations (i.e., multi-dimensional distributions) can themselves be used directly for interpretation or, alternatively, they may be used to guide the selection of parameters for model-based processing such as MRF. It is important to recognize that the MEP technique as well as the methods to interpret D-T2 maps are applicable to both CPMG (Carr, Purcell, Meiboom, and Gill) and DE (diffusion editing)3 measurements.

Engineers face many challenges in deciding how to complete Pre-Salt, carbonate reservoirs offshore Brazil. These challenges include: predicting reservoir performance; evaluating well productivity; determining the best completion design strategy; and finally, determining the best matrix stimulation techniques. Matrix acidizing is a common approach to enhance production from carbonate reservoirs. Well defined wormholes bypass near wellbore damage and provide greater reservoir productivity. Poorly known microbial carbonate can impact acidizing diversion and effectiveness in such rock. Optimizing the stimulation process by perforating and acidizing in the correct way in such high-cost projects is a crucial issue for improved well productivity. This paper discusses how effective perforation design positively impacted the evaluation (Well Testing) and acidizing efficiency in such formations. Results from pre and post matrix acidizing PLT logs and transient analysis from downhole and surface well test data demonstrates perforating design efficiency and how it aides in diverting acid over the entire interval compared to another well in the same field.

Engineers face many challenges in deciding how to complete Pre-Salt, carbonate reservoirs offshore Brazil. These challenges include: predicting reservoir performance; evaluating well productivity; determining the best completion design strategy; and finally, determining the best matrix stimulation techniques. Matrix acidizing is a common approach to enhance production from carbonate reservoirs. Well defined wormholes bypass near wellbore damage and provide greater reservoir productivity. Poorly known microbial carbonate can impact acidizing diversion and effectiveness in such rock. Optimizing the stimulation process by perforating and acidizing in the correct way in such high-cost projects is a crucial issue for improved well productivity. This paper discusses how effective perforation design positively impacted the evaluation (Well Testing) and acidizing efficiency in such formations. Results from pre and post matrix acidizing PLT logs and transient analysis from downhole and surface well test data demonstrates perforating design efficiency and how it aides in diverting acid over the entire interval compared to another well in the same field.

Much has been written about carbonate reservoir complexities, heterogeneity, and data integration at different scales. However, there are not many published examples that show a comparison of producibility modeling predictions and actual field results that include data from core, advanced openhole well logs, formation testers, and drillstem tests.In this study, we present the integration of data and measurements from advanced technologies to evaluate reservoir heterogeneity of carbonate formations on multiple scales. Quantitative textural analyses based on a comprehensive suite of petrophysical logging measurements were integrated with core data and formation testing data to characterize hydrocarbon/water transition zones and formation permeability and producibility. The offshore carbonate reservoir studied is composed of limestones and dolomites. Despite the inherent chemical complexities and hidden modes of origin, dolomites often exhibit favorable reservoir quality with high porosity and permeability properties. For this reason, E&P companies continue to predict where drilling targets are most likely to encounter these sweet spots.Traditional permeability correlations are not effective in these systems, leading to overdependence on porosity-based reservoir descriptions to predict fluid flow. Using nonparametric regression, we have established a relationship between permeability and porosity from logs that are available fieldwide. Subsequent integration of this data with interval pressure transient test data in zones selected based on the observed rock heterogeneity enables further optimization of the final permeability correlation. The descriptions of the field examples confirm the success of this integrated approach and include the planning, real-time monitoring, and final validation of permeability and anisotropy at different scale during the exploration phase of a field.Selecting the well locations for development using the proposed approach has proved valuable for improving field development practices. The results have led to enhanced reservoir characterization based on flow (permeability) and storagecapacity analyses (porosity partitioning), and a better understanding of the reservoir heterogeneity at different scales; the results have been used to improve drillstem test designs and reservoir production strategies.