This paper has an objective of identifying the nature of formation fluid from an extreme tight fractured reservoir. A good understanding of petrophysical properties of the reservoir rock as well as the fluid it contains constitutes a real challenge for tight reservoirs, that are the most common unconventional sources of hydrocarbons. The front-line characterization mean is the Wireline logging which comes directly after drilling the well or while drilling, knowing that for low to extreme low porosity-permeability reservoirs any attempt of conventional well testing will not bring any added value not rather than a confirmation of reservoir tightness. A tailored workflow was adopted to design the most appropriate formation testing module, select the best depths for fluid sampling, and distinguish hydrocarbon from water bearing intervals. This workflow involves ultrasonic and Electric Borehole Images in combination with Sonic Scanner for natural fractures detection, localization and characterization, integrating Dielectric recording and processing for petrophysical evaluation, then Formation Testing was carried out for fluid identification and sampling. The use of borehole electric and sonic imager coupled with advanced sonic acquisition helped not only to identify the natural fractures depths, but also the nature of these fractures. This integration was used for selecting the sampling station.
Wireline formation tests are a critical piece of the exploration and appraisal process, yet they come with a degree of uncertainty. The supermajor has tapped a new software developer to see if it can clear things up. The technology is being proven in millions of phones and homes across the world. Now, a small group of software startups wants to introduce chat bot technology to oil and gas professionals. The same tools that make it fun and easy for you to see a friend's updates online are also pretty good at tying together unconnected databases holding valuable well information.
Formation Testing While Drilling (FTWD) has a broad interest in all the different disciplines involved in drilling and evaluating the well. For the drilling engineer and the geologist, a number of different approaches to the problem of acquiring formation-pressure data while drilling have been tried. Real-time formation-pressure data will, at a minimum, allow more-frequent calibration of pressure models. For the reservoir engineer, it opens the possibility of "barosteering"; where there is doubt in mature fields about whether a compartment has been drained, immediate measurements can be taken, and a decision can be reached about whether to geostop or geosteer for a more-promising compartment. It allows immediate testing to verify whether geological barriers are sealing, and it opens the possibility of pressure profiling to identify (from gradient information) types of fluids present and contact points.
Selecting the best tool for a specific type of reservoir condition is a crucial part of a fluid sampling job. Moreover, uncertainty in sample quality increases when the fluid phases are miscible. On a recent logging job, a formation tester was used to acquire water samples across a zone drilled with water-base mud (WBM). We examine the performance of several probe configurations (both existing and prototype) under equivalent reservoir conditions to quantify and optimize filtrate cleanup efficiency. The study is carried out using a compositional simulator for a water-saturated reservoir invaded with blue-dye tracer included in WBM filtrate.
History matching of field measurements allows the calibration of the model for further modification to account for a variety of reservoir conditions. Complex tracer dynamics of a blue-dye WBM invading a water-saturated formation and fluid pumpout are accurately and expediently modeled using a flexible numerical algorithm to account for different probe types and tool configurations. Under normal operating conditions, the chosen formation tester would have taken around one hour to clean the filtrate contamination to a target value of 5%. On the other hand, the best choice was the Focused Elliptical Probe, for which fluid cleanup would take less than 40 minutes. Additionally, a different tool configuration with a combination of multiple probe geometries spaced radially around the tool would provide faster cleanup times of only 32 minutes, thereby saving rig time.
We rank eight formation testing tools designs under equivalent reservoir conditions. The examples highlight the importance of probe geometry and configurations together with reliable and expedient numerical modeling during the pre-job phase to reduce cleanup time in anticipation of complex reservoir conditions. Furthermore, numerical simulations compare the fluid cleanup efficiency for various commercial formation-testing probes together with innovative probe designs that could potentially lead to a new tool or probe development. Perfecting both probe geometry and fluid pumping schedule is the most important output of our study.
This paper presents a novel methodology to successfully maximize sampling and scanning of formation fluids using formation mapping-while-drilling (FMWD) technology in real time when drilling poorly consolidated formations. The methodology, based on a solid workflow built on experience garnered and captured in various operations and geomechanical studies performed around the world, can be applied in a wide range of wellbore geometries and formation types.
The methodology is based on four processes: 1. Predict, assess, and confirm potential fines migration and formation collapse during FMWD operations. The analysis is based on processing and interpreting existing geomechanical properties from offset wells and real-time newly acquired sonic and/or density data. 2. Design FMWD operations such that formation sanding is prevented, and formation integrity is maintained. 3. Prevent mobilized fines from entering the FMWD tool if partial formation collapsing occurs. 4. Focus the workflow on reducing the negative impact solids will have on the flowline, pump out, and optical analyzers if fines enter the tool.
The paper contains two case studies in which the methodology workflow resulted in successful sampling and real-time downhole fluid analysis of formations with very limited diagenesis and a history of sanding and collapsing during formation testing-while-drilling operations. These two case studies show how assessing offset wells during the planning phase and applying this workflow while evaluating logging while drilling (LWD) petrophysical data in real-time provide a quick insight into how a formation will respond during pump out. The results define station depth selection, timing of the operation with respect to wellbore exposure time, and pump out rate strategy. The application of fixed-rate pump out or intelligent pump out with a fixed differential can then be applied based on the real-time indicators. Specific screen sizes are selected in advance, which limit ingress of fines into the sampling tool. In both case studies, the operating company's objectives were met. An additional case study is presented in which the risk of sanding was not perceived, and no qualification of un-consolidation had taken place, ultimately resulting in formation breakdown in the sampling phase, mobilization of fines, and plugging of the tool; thus, highlighting the value of the novel methodology.
The innovation of this workflow is its holistic approach to sampling while drilling in unconsolidated formations, extensively covering both job planning and execution phases. Additionally, the workflow allows for optimizing tool configuration, and by risk identification, suggests a variety of measures to eliminate or mitigate the impact of partial formation collapse. This workflow extends the application of fluid mapping and sampling while drilling into operational environments, which were previously considered highly unsuitable for this technology.
The reservoir compartmentalization structure and fluid contacts of a field are essential for determining the value of a reservoir asset and provide the two primary purposes of pressure gradient determination. Several new straightforward data-analytical methods have been developed to extract pressure gradient information based on physical properties of the reservoir and meta-analysis of derived pressure gradient information. These methods can be used to provide near real-time feedback about the pressure measurements quality.
This paper describes two distinct methods to determine reservoir compartmentalization structure and fluid contacts. The first method implements statistical evolution to rapidly identify pressure gradients. The second method transforms identified pressure measurements into a meta-analytical visual representation of pressure gradients vs. depth with additional input from measurement consistency. Both methods rely on the accurate removal of pressure outlier data, such as that attributable to supercharging. A new technique using expert knowledge of physical constraints was implemented for reliable outlier removal. The two methods then diverge in subsequent conditioning of the data, but re-converge in adapting an efficient fitting method to extract the desired information.
Both methods provide reliable removal of pressure data that are not related to formation fluid densities, regardless of reservoir number, fluid number, or fluid type. To date, the removal procedure removes more than 95% of outliers and retains more than 90% of accurate pressure data. Both methods also return the correct number and types of fluids. Although pressure gradient estimation can vary by up to 50% for fluid zones of less than 50 ft, the estimation error of the pressure gradients is reduced to less than 3% for fluid zones greater than 100 ft. Furthermore, fluid breaks can be calculated to within 8 ft for the statistical evolution method and to within 30 ft using the visual method. Finally, although the statistical evolution method is markedly faster than the visual method, both techniques provide feedback within a few minutes.
The methods discussed provide feedback about the necessity to retake or take more pressure data during formation-pressure surveys within minutes. This feedback eliminates the delay in reservoir property estimation and greatly increases the reliability and quality of pressure data obtained. The methods presented also use a new application of data meta-analysis to reduce processing time and increase reliability.
Padhy, Girija Shankar (Kuwait Oil Company) | Kasaraneni, Pruthvi Raj (Kuwait Oil Company) | Al-Rashidi, Tahani (Kuwait Oil Company) | Tagarieva, Larisa (Weatherford Oil Tool Middle East Ltd) | Abba, Abdessalem (Weatherford Oil Tool Middle East Ltd)
Carbonate Reservoir characteristics and fluid properties can vary among multiple layers within the same stratigraphic unit. The objective of this case study is to emphasize the added values of integrating the data from a newly introduced formation testing technology along with open hole logs and core data to enhance the understanding of the Minagish Ooilte reservoir permeability distribution and fluid typing.
The methodology implies the first time application of the newly introduced formation testing techology external mounted quartz pressure gauge and fluid typing sensors (density, viscosity, resistivity, capacitance, pressure and temperature), which could minimize reservoir fluid samples contamination and later validated by comparison to laboratory analysis results. The fluid sampling operation was conducted in different reservoir units with varying mobility values where the tested zones were selected based on the pressure pretests done prior to the sampling deployment. The success criteria to evaluate the pressure measurements capability of the new techgnology was met as set by the operator to have accuracy within 0.1psi range for two build-up in pretest at the same point. The data was integrated with open hole logs and laboratory measurements to provide a comprehensive formation evaluation and conclusive reservoir characterization after validation of the permeability.
Heterogeniety in permeability measured/captured through RFT-tool was helpful to understand the reservoir flow capacity at the well location and subsequently select the right perforation intervals. Multiple fluid samples collected during this job aided in understanding the compositional variation with depth in the reservoir. Conjoining fluid variation with flow capacity of the reservoir was immensely useful to understand the true oil potential of the well and eventually select right production allowables. Production performance and productivity of the resulting well obtained after completing in the appropriate interval is better than other wells in the near vicinity.
The high well performance and productivity reflect the value of the information provided by the novel formation testing technology sonde helped, as it achieve the well objectives, design the appropriate completion and most importantly resolve many Minagish Oolite reservoir characterization uncertainties in a timely efficient operation.