The growing demand for oil has emboldened producing companies to reenter old wells to further improve productivity and recovery. This requires monitoring the water saturation. Successes in reservoir saturation monitoring petrophysical analysis have increased the confidence to drill sidetracks in watered wells that have bypassed oil potential. Several techniques can be used to perform the analysis.The Pulsed Neutron Capture (PNC) log is one of the most popular slim cased hole formation evaluation logging tools, which allow running the surveys without having to pull out the production string. Under the right conditions, the PNC logs can be run periodically in the time-lapse mode to monitor changes in water saturation and movements in the oil-water contact and gas-oil contact.The wellbore environment may change between runs and this can complicate the analysis. For example, the borehole fluids may be different: gas, oil or brines of varying salinities. Also, changes in the downhole completion hardware can require running the logs through different tubular configurations. One has to be cognizant of all these environmental effects and appropriately correct for them to obtain the true formation properties, and to make comparisons between runs in the timelapse analysis.Different vendors use different correction schemes. In this paper we will discuss case studies with a methodology from one Service Company that uses a weighted database approach, which relies on characterizing the tool response in known environments. The paper shows some of the advantages and disadvantages of this technique, and in particular, when the downhole conditions deviate from the characterized environment. Alternative methodologies will be proposed to get the best possible results, based on this study. Finally, examples from Saudi Arabian wells will be shown where the computed capture cross section and neutron porosity were successfully corrected in challenging borehole conditions.
The active mobility of sand particles during the production phase has put extra burden on the efficiency of hydrocarbon extraction for both oil and gas. It plays a significant role on completion design during the drilling phase. Minimizing the effect of sanding has been a major topic to tackle due to the added operational costs and time associated. Unconsolidated sand reservoirs are vastly affected worldwide due to the nature of sand particles accompanying hydrocarbon during the production phase. Sand production poses potential risks for surface and subsurface equipment within the completion design. The objective of this paper is to estimate and quantify the potentials of sand production and wellbore instability using 1-D Mechanical Earth Model (MEM). A clear workflow of the utility of raw petrophysical and 1-D geomechanics modelling data is showcased to aid production and completion operational personnel. Excessive stress concentrated around the wall of a borehole can cause the release of sand particles into the hydrocarbon stream. This process poses risks for drilling and completion operations as it affects the productivity of a well along with potential equipment damage. Unconsolidated sand reservoirs are prone to rock failure which induces the mobility of sand particles. Stress orientation regimes are properly captured by assessing the orientation of current petrophysical data. Acoustic data is also reviewed for proper in-situ rock strength property calculation. Formation pressure testing is vital to the process to estimate pore pressure gradients. Once MEM is finalized, Critical Drawdown Pressure (CDDP) is analytically calculated using the linear elastic methodology to predict sand production. The use of 1-D MEM sand management analysis to predict critical drawdown pressure is vital to avoid equipment damage and production limitations associated with sand production in a weakly consolidated reservoir. A workflow to produce an in-depth critical drawdown pressure analysis captures the changes that might occur for a perforation completion over time as it undergoes depletion. A representation of sand potential prediction and critical bottom-hole flowing pressure as a function of reservoir pressure is to be illustrated in a single depth format which allows for sensitivity analysis. This paper examines the direct impact of the analytical estimation of critical drawdown pressure as a guide to predict the potentials of sand production intervals within a certain reservoir. The mechanical properties, petrophysical raw data, and depletion status are the ingredients to produce a thorough analysis to guide drilling, production, and completion personnel to minimize sand production effects operationally. Further improvement to the model can be made by the integration of production data and reservoir properties that are captured over time.
Rock mechanics utilizes empirical formulas which are based on studies of certain environments. The shortcoming of such criteria is having estimations of rock physical properties with high uncertainty and not field/formation specific. The objective of this paper is to apply a core-log integration to convert dynamic mechanical properties captured from formation evaluation logs and calibrate them with core static data to generate a continuous profile of data with low uncertainty and generate correlations applicable to the specific physical environment. To obtain proper rock mechanical correlations, building a mechanical earth model (MEM) calibrated with core data and stimulation data is essential. Multiple wells drilled in a certain sandstone field with rock mechanical physical tests are analyzed. Multi-arm caliber data is also put in use to establish knowledge about in-situ stress directions. The procedure starts with gathering and filtering acoustic slowness & shear, formation pressure, density, and oriented multi-arm caliper logs. Next, calibration of dynamic to core static mechanical data collected in the lab is established. The geomechanical analysis includes an understanding of the state of stresses in a chosen reservoir along with rock elastic and failure properties. The complied data is then integrated using different workflows to develop Mechanical Earth Model (MEM). The intended rock mechanics correlations include elastic constants (Young's Modulus and Poisson's ratio), and rock failure parameters. Once Mechanical Earth Model (MEM) is established, dynamic logging data and core static data are correlated to produce key rock mechanics elements that are field and formation specific. The correlations include Young's Modulus, Poisson's Ratio, Unconfined Compressive Strength (UCS) correlation, and Friction Angle (FANG) correlation. A range of each rock mechanic element is also highlighted for the specific environment showcasing the limits expected for collapse and fracture. Ultimately, stress profile is generated with low uncertainty highlighting magnitudes of maximum and minimum horizontal stresses along with the given interval.
Mud logging, in essence, is a wellsite operation that investigates, records, and analyzes measurements obtained from the circulating drilling fluid that results in the measurement of cuttings and gas. It plays a vital role in the identification of downhole geological conditions, such as hydrocarbon presence and stratigraphy along with monitoring drilling conditions, to ensure safety of operations and improve efficiency. The objective of this paper is to utilize advanced mud logging analysis characteristics to establish a workflow to potentially identify fractures along an interval. Helium is used as the correlation parameter to potentially indicate fractures along the intended formation. Advanced mud logging provides a quantitative hydrocarbon measurement from the drilling mud rather than the qualitative measurements that regular mudlogging provides. Helium is one of the major components that advanced mudlogging provides and acts as an indicator of permeability in a formation. The process starts with a novel method to utilize helium to be a correlator of fractures within a formation in terms of identification and measurements along with tracking the fracture with time. The combination between current formation imaging procedures and helium readings from mud logs is proven to be a key potential indicator to establish a fracture identification pattern. The utility of the correlated helium readings from mud logging and fractures from formation image logs is a major breakthrough into identifying formation fracture features. Tracking changes of such features in which mud logging readings are used directly as potential indicators of fractures in an anticipated well. Loss of circulation prediction and LCM designs are enhanced directly by this extra knowledge.
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