The significant temperature difference between the fractured and non-fractured regions during the stimulation fluid flow-back period can be very useful for fracture diagnosis. The recent developments in downhole temperature monitoring systems open new possibilities to detect these temperature variations to perform production logging analyses. In this work, we derive a novel analytical solution to model the temperature signal associated with the shut-in during flow-back and production periods. The temperature behavior can infer the efficiency of each fracture. To obtain the analytical solution from an existing wellbore fluid energy balance equation, we use the Method of Characteristics with the input of a relevant thermal boundary condition. The temperature modeling results acquired from this analytical solution are validated against those from a finite element model for multiple cases.
Compared to the warm-back effect in the non-fractured region after shut-in, a less significant heating effect is observed in the fractured region because of the warmer fluid away from the perforation moving into the fracture (after-flow). Detailed parametric analyses are conducted on after-flow velocity and its variation, flowing, geothermal, and inflow temperature of each fracture, surrounding temperature field, and casing radius to investigate their impacts on the wellbore fluid temperature modeling results.
The inversion procedures characterize each fracture considering the exponential distribution of temperature based on the analytical solutions in fractured and non-fractured regions. Inflow fluid temperature, surrounding temperature field, and after-flow velocity of each fracture can be estimated from the measured temperature data, which present decent accuracies analyzing synthetic temperature signal. The outputs of this work can contribute to production logging, warm-back, and wellbore storage analyses to achieve successful fracture diagnostic.
Digital core generated from micro CT images of rock sample cutting and results obtained from digital core analysis are presented in this work as a substitute of conventional core study for Petrophysical evaluation. Conventional core extraction during drilling, core preservation and analysis are expensive, time consuming processes and often unavailable for small size fields. Moreover, routine and special core analysis results are a critical input for petrophysical characterization. In this situation, digital core study appears to be a cost effective substitute to ensure and validate petrophysical evaluation results.
High resolution 3D micro CT imaging and analysis was done on rock samples cut during drilling or on sidewall core plugs cut by wireline logging tool. Segmented micro CT image slices when combined in 3D space in three orthogonal directions, can be termed as digital core. Solid rock matrix, clay filled and porous rock portions are distinctly separable using micro CT images and their volume fractions can be estimated. Detail textural analysis in terms of Grain and pore throat size distribution of the rock is possible from digital core which controls storage capacity and flow behavior. Two critical petrophysical input parameters for fluid saturation (Sw) estimation are cementation exponent (m) and saturation exponent (n). These parameters are commonly computed from special core analysis (SCAL) on conventional core plugs. But digital core study can provide the estimates of ‘m’ and ‘n’ which replace the need of SCAL.
Digital core study has been carried out in three different reservoirs in west and east coast of India and the results were analyzed. Porosity and permeability data obtained from digital core was first compared with log analysis results and then used to identify different petro physical rock types (PRT). Fluid saturation (Sw) was estimated from resistivity log by using ‘m’ and ‘n’ exponent obtained from digital core seems to be more realistic and corroborates with well test results. Porosity, permeability, water saturation and rock types (PRT) were helped to build geo-cellular model (GCM) for small and marginal reservoir.
Enhanced reservoir characterization by using digital core study result has helped in better understanding and decision making for small and marginal fields where limited well data is available. Finally this leads to the preparation of field development plan (FDP). Digital core technique is less expensive, having quick turnaround time than conventional coring which has translated into high value business impact for any development project.
Gupta, M K (Oil and Natural Gas Corporation Ltd.) | Sukanandan, J N (Oil and Natural Gas Corporation Ltd.) | Singh, V K (Oil and Natural Gas Corporation Ltd.) | Bansal, R (Oil and Natural Gas Corporation Ltd.) | Pawar, A S (Oil and Natural Gas Corporation Ltd.) | Deuri, Budhin (Oil and Natural Gas Corporation Ltd.)
This paper discusses a case study of one of the onshore field of ONGC where while processing well fluid, frequent surge has been observed leading to shutdown of the SDVs creating severe operational problems and loss of production. It was imperative to find out the problematic wells/lines located in clusters which contribute for surge formation and mitigation approach with minimum modifications.
A transient complex network of sixty five wells flowing with a different lift mode such as intermittent gas lift, continuous gas lift etc were developed in a dynamic multiphase flow simulator OLGA. Time cycle of each well were introduced for intermittent lift wells. Simulation study reveals pulsating transient trends of liquid flow, pressure which was matched with the real time data of the plant and hence confirms the accuracy of the model. After verifying the results, different scenarios were created to determine the causes of surge formation. After finding the cause, a low cost approach was considered for surge mitigations.
An integrated rigorous simulation was carried out in OLGA, by feeding more than 12,000 data points to obtain model match. Several scenarios were also created such as optimization of lift gas quantity, optimization of elevation and size. Trend obtained after each scenario was pulsating behaviour and it matched with the real time data appearing in the SCADA system of the field. After rigorous simulation with each scenario, it was established that the cause of surge forming wells/pipelines. Once the root cause of surge has been confirmed then quantum of liquid generated due to surge was determined. Adequacy checks of the existing separators were carried out to estimate the handling capacity of the existing separators at prevalent operating condition. After adequacy check it was found that existing separators cannot handle the surge generated in that time interval leading to cross the high-high safety level, resulting closure of shut down valve (SDV). After establishment of root cause of the surge, a low cost solution with small modification in pipelines and control system/valves was adopted to arrest the surges. It was first of its kind simulation carried out for a huge network of wells/ pipelines by feeding more than 12,000 data to analyze the surge formation cause and capture its dynamism owing to wide array of suspected causes. This will help to address the challenges of efficiently reviewing the entire pipeline network while designing new well pad/GGS and will also help to arrest surge by adopting a low cost solution wherever such situation arises.
Baker Hughes drilled one horizontal well for major Indian operating company in a, low resistivity contrast field, onshore India. The candidate field / basin is a proved petroliferous basin, located in the northeastern corner of India.
The scope of work for this project involved integrating geological and open hole offset parameters to build a Geosteering model. Integrated data included a study of offset well data from the field, regional and local dip analysis from wellbore images, and a review of structural maps. Successful integration of these data helped to steer the well in the desired zone as per plan and make the best use of the data and to reduce uncertainties in Geosteering, drilling. Although high-quality 16-sector images commonly yield bedding dip, fracture and other geological information, this paper emphasizes how real-time reservoir navigation decisions was made using Geosteering modelling, real-time image processing, dip picking study etc.
Kisku, Sayanima (Oil & Natural Gas Corporation Ltd.) | Santhosh Kumar, R. (Oil & Natural Gas Corporation Ltd.) | Dayal, Har sharad (Oil & Natural Gas Corporation Ltd.) | Chadha, Harish Kumar (Oil & Natural Gas Corporation Ltd.) | Srivastava, Anil (Oil & Natural Gas Corporation Ltd.)
Infill drilling is an integral part of brown field management for exploiting un-drained areas with good oil saturation. In a matured field on water-flood, the primary objective is optimized wellbore placement of infill wells in areas with better petro-physical characteristics, bypassing flooded region. It is also important to design a robust completion strategy to safeguard the longevity of these wells by curtailing produced water. This approach assists in dramatic increase in production by isolating water charged sections and thereby restricting rise in water production.
The use of advanced Logging-While-Drilling techniques during horizontal drilling provides an opportunity for effective well planning. Real-time Logging-While-Drilling instruments during directional drilling gives us the opportunity to acquire information pertaining to the reservoir in a single run. Interpretation from the real-time data acquisition boosts the planning during wellbore drilling.
This paper discusses a case study of a field in western offshore, India, which focuses on the applications of geosteering and the use of swell packers for zonal isolation to augment oil production. In this study, two wells have been deliberated where the real-time information has been extracted and included in the decision making process. The bottom-hole assembly used in this case, comprised standard Logging-While-Drilling services such as gamma ray, resistivity, neutron porosity, density and density imaging services and also formation pressure testing.
Since the field under study is a carbonate reservoir that has been on waterflood for the last twenty eight years, chances of early breakthrough of water in the infill wells has posed a high risk in spite of the presence of good bypassed oil saturation. Geosteering has enabled to restrict the horizontal section safely within the desired zone of better oil saturation and geological features, as interpreted from the Logging-While-Drilling data. Further isolation of suspected water bearing zones with swell packers have assisted in healthy well completion by diminishing chances of sharp rise in water cut in the infill wells.
Using optical fibers to instrument hydraulically fractured wells is becoming routine in US unconventional plays. Instrumented wells facilitate understanding of proppant distribution among perforation clusters and the inefficiencies of geometric fracturing and well planning techniques. However, converting fiber-optic data into proppant distribution requires management of high volumes of data and correlation of the data to factors such as well conditions, fracturing parameters, and temperatures. A user-friendly workflow for understanding hydraulic fracturing proppant and slurry distribution among different perforation clusters over time is presented. Ideally, slurry flow is equal between perforation clusters and, at least, constant in time, but the reality is very different. The interpretation workflow is based on proprietary algorithms within a general wellbore software platform and aims to greatly expedite the analysis. We propose using distributed acoustic sensing (DAS) data (in the form of custom frequency band energy (FBE) logs), distributed temperature measurements (DTS) and surface pumping data to obtain a quantitative analysis of proppant distribution within minutes, with various options for reporting and visualizing results. The software platform selected provides data integration, visualization, and customization of in-built algorithms. The new workflow enables users to upload DAS, DTS, flow rate, pressure, and other measurements and use customized algorithms to quantitatively analyze proppant distribution, enabling decisions in real time to optimize the fracturing operation. The validity of the approach is illustrated by a case study involving a well with 28 stages and four to five clusters per stage. The workflow is automated to provide results in real time, enabling quick corrective actions and significantly improving the efficiency and economics of hydraulic fracturing.
As the oil and gas industry is moving towards digital oil field, the selection of leak detection system (LDS) has become more crucial. Early detection of leaks not only saves environment from Hazardous hydrocarbons but considerable loss in production is also saved. This paper discusses about both internal and external LDS and its applicability for onshore and offshore fields. This paper will ease the selection process of LDS for green and brown fields of both offshore and onshore installation.
Monitoring and reevaluation of petrophysical attributes in a mature field under production for many decades is crucial for optimizing production and further development planning. In this case study, a multidisciplinary approach is deployed for formation evaluation and reservoir characterization using logging-while-drilling (LWD) sensors spanning formation volumetrics, fluid analysis, high-resolution image interpretation, and geomechanics to confirm remaining oil saturations and help identify recompletion intervals. LWD technologies were used in four wells in Sahmah field of Oman to provide an integrated petrophysical and geomechanical field study using a bottomhole assembly (BHA) including gamma ray, resistivity, formation bulk density, thermal neutron, acoustic, high-resolution imaging, and formation pressure testing sensors. A deterministic multimineral petrophysical model was used to derive formation volumetrics and fluid analysis. Geomechanical interpretation used high-resolution microresistivity imaging, acoustic slownesses, and formation pressure data to verify principal stress orientations and to quantify pore pressure and horizontal minimum and maximum stress magnitudes. These data were then correlated with historical data to evaluate sweep efficiency and residual fluid saturations. LWD sensors have proven to provide robust geological, petrophysical, and geomechanical data compared to previous traditional wireline data acquisition.
While distributed temperature sensing (DTS) has become a commonly used tool in reservoir studies, the technology has not seen widespread use in SCAL projects. Most core-scale experiments attempt to control temperature at a constant value rather than monitor temperature changes within a sample during a test. High-resolution temperature arrays are available that measure changes in temperature of 0.1°C at 1-mm resolution. The optical backscatter reflectance (OBR) fiber senses both temperature and strain that can be separated through experiment design and signal processing. These OBR fibers are sensitive enough to monitor temperature changes associated with endo- and exothermic chemical reactions associated with mineral dissolution/precipitation, or fluid-front movements in steam-assisted gravity drainage of heavy-oil tests. An example of the use of a distributed temperature array is in the monitoring of natural-gas-hydrate formation and dissociation in a sandpack as CO2 is exchanged with the naturally occurring CH4 in the hydrate structure. A fiberoptic array was placed within a narrow-diameter PEEK tube as the sandpack was constructed. The PEEK tube held the fiber optic in place so that the sensed signal was temperature only and did not include any strain effects. The OBR was set up to acquire a temperature array every 30 seconds during the test at 5-mm spacings. The core holder was placed in a MRI instrument that provided additional spatial information on hydrate formation during the test that was compared with the OBR results. Initial hydrate formation resulted in a several degrees increase in temperature at the inlet end of the cell that with time, progressed down the length of the cell. The temperature array and MRI images both showed the nonuniform nature of hydrate formation and subsequent dissociation of the hydrate when N2 was injected into the cell as a permeability enhancement step. The faster response of the OBR array compared to the time required to acquire MRI images provided additional detail in the sequence of hydrate formation and dissociation during CH4-CO2 exchange. The limitation to the OBR array was that it only sensed temperature fluctuations proximal to the fiber as a function of the hydrate system’s thermal conductivity.
Image processing of high-resolution 3D images to create digital representation of pore microstructures for image-based rock physics simulations remains a highly subjective enterprise, despite the seemly precision associated with improving imaging resolutions and intensive parallel computations. The decisions on how to identify pore space, both macro- and micropores, and various mineral components remain very much dependent upon user choices and biases. This study demonstrates how uncertainty can be quantified for a highly subjective segmentation process. A set of shaly sand samples with significant amounts of authigenic chlorite/smectite that lines larger pores was tested to identify uncertainty quantification (UQ) requirements associated with image-processing steps, segmentation in particular. Much of the porosity in these coarse-grain samples is associated with subresolution micropores that complicates their assignment in any pore-grain segmentation strategy. Two segmentation strategies, a binary segmentation with a linear-threshold and a machine-learning (ML) approach to two-phase segmentation, are employed with different UQ parameter space. The contribution of resolvable macropores in these samples, and their spatial distributions with regard to pore-lining clay mineral with unresolvable microporosity, are iteratively studied over the defined UQ parameter space, and cross-validated by independent NMR and MICP measurements. The pore structure extracted from these different iterations was the basis of simulations for basic petrophysical properties. Upon cross-validation of simulated results with measured core properties, a UQ framework is proposed to assess the differences between the different measurements from three angles: sampling, numerical and physical.