Malleswaram field in Krishna-Godavari (KG) basin has proven gas reserves in the late Cretaceous Nandigama formation. Many drilling challenges were faced, including losses, tight hole, and stuck pipe in the Raghavapuram and Nandigama formations overlying the reservoir interval. This study was conducted to provide a solution for drilling optimization by mitigating drilling-related nonproductive time (NPT). Integration of acoustic and geochemical data for geomechanics study provided a new insight into cause of overpressure and need for revamping of casing policy to significantly improve wellbore stability, mitigate risks, and ensure future drilling success. Generated stress models can be used to optimize hydraulic fracturing in these reservoirs. A completion quality based on stress model indicates the need for multistage fracturing due to the presence of stress barriers inside sand units in Nandigama formation.

With all the conventional reservoirs being almost exhausted around the world, our immense dependency on unconventional reservoirs has led us to look for measurements that are beyond conventional way. In the optimal exploitation of unconventional reservoirs, integrated Petrophysical and Geomechanical studies provide the best means to both 1) evaluate formation properties such as fluid types, volumes and flow potential, and 2) use this information along with rock's mechanical properties to optimize completions program and maximize production. While a basic petrophysical study can be made using triple combo logs gamma ray, neutron porosity, density and resistivity - for reconnaissance and quick look, such studies are not enough for the purpose of completions and production optimization in unconventional. A combined study using different petrophysical, geological and acoustic logs is used in order to answer the questions and problems faced during characterizing a tight unconventional reservoir. The answer products from these will help in advanced studies which would include reservoir characterization and completion design. For that, we would need to bring in acoustic measurements to determine rock types and respective mechanical properties, which would be influenced by fracture, anisotropy, stress direction and permeability of the formation. Spectroscopy logs will further add to knowledge of the lithology at mineral level, required for petrophysical evaluation and rock physics modeling. Today advanced spectroscopy logs also measure Total Organic Carbon (TOC) percentage of the formation, important to understand source rock maturity and to determine true flow potential in tight formations. Images from Micro Imaging resistivity tool are important in unconventional to evaluate fractures which often times are the only source of permeability in tight rocks. Nuclear Magnetic Resonance is considered essential to determine fluid types, respective volumes and bulk permeability of unconventional formations. An integrated study using all the above measurements helps best combine Petrophysical and Geomechanical aspects of the formation under investigation. Furthermore, in unconventional reservoir evaluation, such a study helps us to determine stress barriers to hydraulic fracturing important to zone-wise design and optimize completions program. In this paper, we present a systematic procedure and corresponding results of an Integrated Petrophysics and Geomechanics study in an unconventional tight reservoir, which helped to 1) optimize hydraulic fracturing and completions program, and 2) create complete model of hydrocarbon production.

The Spraberry trend area is part of a larger oil-producing region within the Midland basin in United States. The main targets, Spraberry, Dean and Wolfcamp, are reservoirs of shales interbedded with clastic formations. Thus, the reservoirs exhibit TIV (transverse isotropy vertical) anisotropy due to thin laminations. A pilot well was drilled vertically in the complex lithology and logged with the advanced acoustics measurements. Shallow penetration of Stoneley energy into the formation raised concerns about the depth resolution of the inverted shear slowness derived from it. It is very difficult to get a reliable horizontal shear slowness from Stoneley when the borehole condition is rugose, there is a complex mud rheology and gas influx inside the borehole. A machine learning based approach integrating the advanced acoustics measurements and petrophysical interpretation is adopted to provide the solution to get the lithology-based horizontal shear slowness. To eliminate the variability of getting the horizontal shear slowness from Stoneley wave, to process for an advanced geomechanics product like for TIV anisotropy analysis, two machine learning algorithms are used. First one is a very commonly used linear supervised learning algorithm multi-linear regression (MLR) and second is random forest (RF) a nonlinear supervised learning algorithm. These algorithms take inputs from formation evaluation and advanced acoustics to predict the horizontal shear slowness. The random forest algorithm being an ensemble learning method have greater predictive capabilities compared with any linear supervised learning models and many of the non-linear supervised learning algorithms. The inputs for RF and MLR regressions are values of dry weight fractions of calcite, dolomite, quartz, illite, total porosity, permeability, gamma ray, compressional slowness and fast shear slowness. These values are obtained for the entire depth of interest from advance logging tools and interpretation techniques. To check the performance of the model, standard machine learning techniques such as the error evaluation metrics of the mean squared error and the coefficient of determination (R-squared or R2) were considered. The model has been trained over 90% of data and 10% of the data was used to cross-validate the model. Hyperparameter tuning of the RF model has been done to improve upon the prediction accuracy. After the parameters are tuned, the mean squared error and R2 value of the training dataset are 1.77 and 0.98; while that for the testing dataset, they are 13.26 and 0.89 respectively. The closeness of the R2 value for both the training and testing dataset to 1, implies that the RF model is successfully able to explain the variance of the given data.

Borehole resistivity images and dipole sonic data analysis helps a great deal to identify fractured zones and obtain reasonable estimates of the in-situ stress conditions of geologic formations. Especially when assessing geologic formations for carbon sequestration feasibility, borehole resistivity image and borehole sonic assisted analysis provides answers on presence of fractured zones and stress-state of these fractures. While in deeper formations open fractures would favour carbon storage, in shallower formations, on the other hand, storage integrity would be potentially compromised if these fractures get reactivated, thereby causing induced seismicity due to fluid injection. This paper discusses a methodology adopted to assess the carbon dioxide sequestration feasibility of a formation in the Newark Basin in the United States, using borehole resistivity image(FMI™ Schlumberger) and borehole sonic data (SonicScaner™ Schlumberger). The borehole image was interpreted for the presence of natural and drilling-induced fractures, and also to find the direction of the horizontal stress azimuth from the identified induced fractures. Cross-dipole sonic anisotropy analysis was done to evaluate the presence of intrinsic or stress-based anisotropy in the formation and also to obtain the horizontal stress azimuth. The open or closed nature of natural fractures was deduced from both FMI fracture filling electrical character and the Stoneley reflection wave attenuation from SonicScanner monopole low frequency waveform. The magnitudes of the maximum and minimum horizontal stresses obtained from a 1-Dimensional Mechanical Earth Model were calibrated with stress magnitudes derived from the ‘Integrated Stress Analysis’ approach which takes into account the shear wave radial variation profiles in zones with visible crossover indications of dipole flexural waves. This was followed by a fracture stability analysis in order to identify critically stressed fractures. The borehole resistivity image analysis revealed the presence of abundant natural fractures and microfaults throughout the interval which was also supported by the considerable sonic slowness anisotropy present in those intervals. Stoneley reflected wave attenuation confirmed the openness of some natural fractures identified in the resistivity image. The strike of the natural fractures and microfaults showed an almost NE-SW trend, albeit with considerable variability. The azimuth of maximum horizontal stress obtained in intervals with crossover of dipole flexural waves was also found to be NE-SW in the middle part of the interval, thus coinciding with the overall trend of natural fractures. This might indicate that the stresses in those intervals are also driven by the natural fracture network. However, towards the bottom of the interval, especially from 1255ft-1380ft, where there were indications of drilling induced fractures but no stress-based sonic anisotropy, it was found that that maximum horizontal stress azimuth rotated almost about 30 degrees in orientation to an ESE-WNW trend. The stress magnitudes obtained from the 1D-Mechanical Earth Model and Integrated Stress Analysis approach point to a normal fault stress regime in that interval. The fracture stability analysis indicated some critically stressed open fractures and microfaults, mostly towards the lower intervals of the well section. These critically stressed open fractures and microfaults present at these comparatively shallower depths of the basin point to risks associated with carbon dioxide(CO2) leakage and also to induced seismicity that might result from the injection of CO2 anywhere in or immediately below this interval.

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