Sand production in unconsolidated formations during sampling can lead to poor quality of samples being acquired due to plugging of flow lines and sealing issues at the probe. Formation pressure and mobility measurements can also be affected by sand production which may cause plugging inside the tool or at the tool inlet and result in increased operational time. Predicting sanding potential thus becomes critical to achieve both operational and formation characterization objectives, especially in deep-water environments, where operation costs are high. Calculating "Critical Draw Down" (CDD) pressure and predicting the sanding envelope through geomechanical-sanding analysis provide insights critical to successful testing and sampling operation. A fit for purpose geomechanical model has been developed based on petrophysical data along with regional knowledge of geomechanical conditions. With the geomechanical model, analytical sanding evaluation is used to calculate a range of CDD values for the likely testing and sampling points using well logs from offset wells. Logs from the studied well are analyzed in real time to update CDDs. The zones least prone to sand production are identified and prioritized for testing and sampling. The pre-drill sanding risk assessment is also used to optimize operational parameters including selection of the best pump and packer types while the real time updated CDD values is incorporated to limit the flowing (drawdown) pressures during the sampling and testing operations. A case study from a deep-water field in India is highlighted where the mentioned workflow developed post logging for a pilot wellbore has helped to optimize decisions in real time during formation pressure testing and sampling in its sidetrack wellbore, thus adding value to reservoir characterization objectives and reducing nonproductive time (NPT). Based on the pre-drill sanding assessment, CDD was found to be in the range of 0 - 500 psi below the formation pore pressure in some of the sand bodies. Also, a large face packer was recommended to enhance sealing efficiency by increasing the contact area with the formation. Pump rate was regulated during pressure testing and sampling to ensure that the pressure never exceeded the pre-defined CDD values thus preventing sand production. Multiple fluid samples were collected successfully without any plugging. This integration of geomechanical assessment with operation contributed to 32% increase in success rate for good quality pressure testing and acquisition of representative samples in the sidetrack wellbore, benefitted from a systematic adaptation of pre-job assessment and real time optimizations compared to the pilot wellbore. The pre-drill petrophysical and geomechanical evaluations provide critical insights to assist in real time optimization of pressure testing and fluid sampling operations in unconsolidated reservoirs. Workflow presented in this paper has proven to be valuable in obtaining reliable formation pressure data and contamination-free formation fluid samples for accurate reservoir and fluid characterization in unconsolidated formations during wireline logging testing and sampling operations.

Fluid samples collected using either wireline or logging-while-drilling (LWD) formation-testing technology for reservoir fluid characterization have long been accepted as the most representative of reservoir fluid. This, though, comes with a caveat that the collected sample is clean and devoid of any mud-filtrate contamination. With both techniques performed soon after drilling a well, there is always a risk of contaminating the collected fluid with mud filtrate. Toward the goal of reducing this risk, since the early 2000s, technologies have been brought forth to help identify the fluid down hole. There have been multiple developments with sensors for absorbance spectroscopy, fluorescence, fluid resistivity, fluid refractive index, and so on. Each sensor development was targeted toward a specific fluid interaction with the mud filtrate, thereby helping to differentiate the reservoir fluid from the mud filtrate. Downhole sampling conditions can be classified into two broad groups: one case where the reservoir fluid is miscible with the mud filtrate and the other where the reservoir fluid is not miscible with the mud filtrate. The immiscible cases are generally straightforward, since sensors such as absorbance spectroscopy can easily differentiate among oil, water, and gas. In addition, the technique can be used to determine the fractional portion of each phase in the flow. Complications arise when the reservoir fluids happen to be miscible with the mud filtrate system; for example, while sampling reservoir water in the presence of water-based mud filtrate, absorbance spectroscopy by itself is unable to differentiate among the fluids. Table 1 provides generic information about different fluid systems as well as the sensors used to differentiate the fluids. While there are other sources of correlation-based fluid-property information, the basic sensors mentioned are the ones used for correlations. As mentioned, each sensor provides detailed information for specific cases, but only sound speed provides a single-sensor solution for the conditions expected. Sound-Speed (SS) Measurement While acoustic data have long been used for reservoir characterization, data have been used for fluid characterization during downhole sampling for only a decade. Experience has shown that this measurement is sensitive enough to not only differentiate injection water or formation water but also to track and quantify small changes in oil compressibility—an important step in focused sampling. The measurement uses a pulse-echo technique based on the principle that an acoustic signal propagates approximately as a plane wave, and that the speed of sound is based on the distance the pulse travels divided by the time it took to traverse the distance. (SPWLA-2013-FFF). The 10-MHz piezoelectric transducer is mounted onto a machined flat surface on the flowline of RCX (the wireline formation testing tool reservoir characterization instrument) as schematically shown in Fig. 1. The travel path length is the distance between the two internal surfaces of the flowline. The result was a bulk measurement of the speed of sound across all the fluid flowing though the flowline. The only calibration needed is for this path length, which can differ due to slight machining variations. A calibrated sensor was able to differentiate fluids which exhibited sound-speed differences as small as 4.7 m/sec (0.5 msec/ft of sound-speed slowness).

Understanding the properties of formation fluid is a critical step in reservoir characterization. The use of Logging While Drilling (LWD) based fluid sampling becomes increasingly important in high risk scenarios. The LWD environment is significantly different from that of Wireline (WL) for sampling operations as the dynamic filtrate invasion is still in effect. LWD sampling is a relatively new technology and its sampling efficiency compared to WL sampling is not well known. This study aims to understand the effects of dynamic invasion processes on LWD fluid sampling and compare its performance with WL based fluid sampling. The results of the simulation study performed revealed that when the wait time after the drilling is optimized, LWD can provide cleaner samples in shorter cleanup time than WL sampling. It also revealed that the reservoir fluid breakthrough time would be shorter in LWD sampling compared to that of WL. This study indicates that with proper modeling, an optimized sampling program can be executed to meet the objectives of the LWD sampling operations in the most economic manner.