What if There Was a Better Formation-Testing Probe? A Case Study on Optimizing Flow Geometry
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Cited by 2 publications
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Optimizing LWD Fluid Sampling With a New Transient Approach: The Reciprocal Contamination Derivative
Successful in-situ fluid cleanup and sampling operations are commonly driven by a fast and reliable analysis of pressure, rate, and contamination measurements. Currently, techniques such as pressure transient analysis (PTA) and rate transient analysis (RTA) provide important information to quantify reservoir complexity, whereas fluid contamination measurements are overlooked for reservoir characterization purposes. The objective in this paper is to introduce a new interpretation technique to relate fluid contamination measurements with reservoir properties by identifying early- and late-time flow regimes in the derivative plots of reciprocal fluid contamination. Among several applications, this new transient analysis method is effective for improving logging-while-drilling (LWD) fluid sampling operations. The derivative methods used in PTA and RTA inspired the development of the new fluid contamination interpretation method. Contamination transient analysis (CTA) evaluates transient measurements acquired during mud-filtrate invasion cleanup to infer reservoir geometry. We apply derivative methods to the reciprocal of the time evolution of fluid contamination to identify flow regimes in cases of water-based mud invading either water-or hydrocarbon-saturated formations. LWD operations are considered under a continuous invasion effect, i.e. the fluid cleanup procedure is performed while mud filtrate continues to invade the formation. This constraint brings about a significant technical challenge for LWD fluid sampling jobs. Alternatively, this new method could be integrated with other pressure transient techniques to improve the interpretation of measurements. For example, in a pretest case where the pressure transient does not achieve the radial flow regime, fluid cleanup could provide complementary information about late-time flow regimes to enhance the acquisition of measurements in real time. We document synthetic and field examples of applications of a new interpretation method. Seven reservoir cases are simulated to obtain contamination data: (1) homogeneous isotropic reservoir, (2) formation thickness, (3) laminated formations, (4) geological faults, (5) mud-filtrate invasion (6) reservoir properties, and (7) permeability anisotropy. All these cases are compared for single-phase and multiphase flow during LWD fluid sampling operations. Additionally, field case studies are analyzed to highlight the value of the reciprocal contamination derivative (RCD) in real-time operations. Reservoir limits and features such as saturating fluid and depth of invasion are identified in the flow regimes detected with derivative plots of the reciprocal of the contamination. Consequently, LWD cleanup and sampling efficiency could be optimized based on contamination transient analysis by identifying the flow regimes taking place in the reservoir during filtrate cleanup, hence improving the prediction of the time required to acquire non-contaminated fluid samples. The new approach of the reciprocal contamination derivative is an alternative way to optimize fluid cleanup efficiency and to quantify the spatial complexity of the reservoir during real-time LWD operations. In addition, this new technique enables the evaluation of reservoir properties in less operational time than PTA without the need of pressure build-up stages, increasing fluid sampling efficiency in terms of quality and time.
Optimizing LWD Fluid Sampling With a New Transient Approach: The Reciprocal Contamination Derivative
Successful in-situ fluid cleanup and sampling operations are commonly driven by a fast and reliable analysis of pressure, rate, and contamination measurements. Currently, techniques such as pressure transient analysis (PTA) and rate transient analysis (RTA) provide important information to quantify reservoir complexity, whereas fluid contamination measurements are overlooked for reservoir characterization purposes. The objective in this paper is to introduce a new interpretation technique to relate fluid contamination measurements with reservoir properties by identifying early- and late-time flow regimes in the derivative plots of reciprocal fluid contamination. Among several applications, this new transient analysis method is effective for improving logging-while-drilling (LWD) fluid sampling operations. The derivative methods used in PTA and RTA inspired the development of the new fluid contamination interpretation method. Contamination transient analysis (CTA) evaluates transient measurements acquired during mud-filtrate invasion cleanup to infer reservoir geometry. We apply derivative methods to the reciprocal of the time evolution of fluid contamination to identify flow regimes in cases of water-based mud invading either water-or hydrocarbon-saturated formations. LWD operations are considered under a continuous invasion effect, i.e. the fluid cleanup procedure is performed while mud filtrate continues to invade the formation. This constraint brings about a significant technical challenge for LWD fluid sampling jobs. Alternatively, this new method could be integrated with other pressure transient techniques to improve the interpretation of measurements. For example, in a pretest case where the pressure transient does not achieve the radial flow regime, fluid cleanup could provide complementary information about late-time flow regimes to enhance the acquisition of measurements in real time. We document synthetic and field examples of applications of a new interpretation method. Seven reservoir cases are simulated to obtain contamination data: (1) homogeneous isotropic reservoir, (2) formation thickness, (3) laminated formations, (4) geological faults, (5) mud-filtrate invasion (6) reservoir properties, and (7) permeability anisotropy. All these cases are compared for single-phase and multiphase flow during LWD fluid sampling operations. Additionally, field case studies are analyzed to highlight the value of the reciprocal contamination derivative (RCD) in real-time operations. Reservoir limits and features such as saturating fluid and depth of invasion are identified in the flow regimes detected with derivative plots of the reciprocal of the contamination. Consequently, LWD cleanup and sampling efficiency could be optimized based on contamination transient analysis by identifying the flow regimes taking place in the reservoir during filtrate cleanup, hence improving the prediction of the time required to acquire non-contaminated fluid samples. The new approach of the reciprocal contamination derivative is an alternative way to optimize fluid cleanup efficiency and to quantify the spatial complexity of the reservoir during real-time LWD operations. In addition, this new technique enables the evaluation of reservoir properties in less operational time than PTA without the need of pressure build-up stages, increasing fluid sampling efficiency in terms of quality and time.
Obtaining representative clean fluid samples in the least amount of rig time is the primary objective for open-hole sampling. The estimation of contamination levels within the pumpout fluid in real time poses major challenges to accomplish this operation, particularly during the early stages of field exploration and appraisal. The objective of this paper is to introduce new real-time monitoring and control algorithms to improve sampling quality and improve estimates of key formation properties such as pore pressure, mobility and relative oil/water saturation effects using machine learning based on an extensive database created from a parametric simulation study. A database can be created from field data but is typically too sparse to be used to create an analysis method, as many of the parameters are unknown. After detailed analysis of formation pumpout cleaning behavior and oil-well sampling, a parametric study was designed and used to conduct an extensive matrix of simulations to generate the comprehensive database. The study was required to determine the sensitivities to various parameters related to sampling and contamination. The results from this database were used to create a new tool for real-time monitoring and control. The database contained the simulated temporal cleaning trends of pumpouts over a variety of reservoir and operating conditions. Parameters affecting the cleaning behavior during the formation testing pumpout were evaluated and incorporated into a three-dimensional (3-D), compositional simulation model. Reasonable variations of the parameters were selected based on a comprehensive study and data from available literature. The parameters included reservoir rock and fluid types, reservoir pressure and temperature, different oil-based muds (OBM), active mud-filtrate invasion, and operating conditions. Nearly one hundred thousand scenarios were evaluated based on full factorial and a one-factor-at-a-time (OFAT) experimental design and were subsequently used to study the effects of each parameter and its variations. Statistical tests, such as mutual information and analysis of variance (ANOVA), were used to determine the significance of different parameters on the simulation results. These simulations reveal a more complex pumpout behavior than has previously been published. This paper discusses the effects of different parameters on the cleaning process and uncertainty analysis for various scenarios. Trends of density and contamination during pumpout are evaluated, and new guidelines and equations are provided for trend-fit cleanup prediction. Additionally, the effect of active mud-filtrate invasion is considered and its effect on endpoint contamination is described (i.e., lowest contamination possible). The workflow and data can be used for pre-job planning as well as during real-time operations with various wireline-formation-tester (WFT) and logging-while-drilling (LWD) tools to optimize cleanup and sampling of formation fluids. Simulations of different realizations of reservoir properties, drilling mud invasion profiles, and cleanup operations also helped develop a useful and diverse cleaning behavior database for data-driven modeling for a variety of reservoir and operating conditions.
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