Forsythe, J. C. (Schlumberger) | De Santo, Ilaria (Schlumberger) | Martin, Robin (Premier) | Tyndall, Richard (Premier) | Arman, Kate (Premier) | Pye, Jonathan (Premier) | O'Donnell, Martin (Premier) | Kenyon-Roberts, Stephen (Premier) | Nelson, Robert K. (Woods Hole Oceanographic Institution) | Reddy, Christopher M. (Woods Hole Oceanographic Institution) | Pomerantz, Andrew E. (Schlumberger) | Canas, Jesus Alberto (Schlumberger) | Zuo, Julian Y. (Schlumberger) | Peters, Kenneth E. (Schlumberger) | Mullins, Oliver C. (Schlumberger)
Reservoirs with multiple processes that impact the quality and distribution of crude oils can be complex. Here, a series of seven reservoirs in the North Sea contain a viscosity profile that is strongly affected by a spill-fill sequence of reservoir charging, biodegradation, water washing, and variation in thermal maturity. Mapping the viscosity gradient and its origins is critical to understand how each factor contributes to the complexity of these reservoirs. Additionally, evaluation of reservoir connectivity is key. Combined studies of downhole fluid analysis (DFA) and high-resolution compositional analysis by comprehensive two-dimensional gas chromatography (GC×GC) can be used to unravel the contributions of various effects and provide an improved understanding of the reservoir. The seven reservoirs examined are consistent with a simple description of the multiple processes that contribute to the viscosity gradient and connectivity analysis. The maturity of charge in this spill-fill sequence has continued to increase with time; consequently, crude oil in deepest reservoir is most mature and the shallowest, the least mature. The oil spills from the oil-water contact (in these injectite reservoirs); consequently, the deepest reservoir is the least biodegraded and the shallowest reservoir the most biodegraded. Observations here are consistent with both biodegradation and water washing being dominated by in-reservoir confinement of the oil as opposed to during migration. The deepest reservoir exhibits mild biodegradation and mild water washing, while the nearby shallowest reservoir exhibits severe biodegradation and severe water washing. Finally, in this spill-fill process, the replacement of new oil for old, especially in the deepest reservoirs, indicates excellent reservoir connectivity.
The paper presents two intelligent intervention systems, deployed on drill pipe and coiled tubing respectively, and showcases how these systems improve intervention efficiency, reduce operational risks and optimize production in mature asset.
Interventions are more challenging than ever, driven by the increased well complexity and reduced margin for error. The conventional intervention approaches, which are mostly experience based and involve significant amount of guesswork, are inadequate. Two new intervention systems, enhanced by real-time downhole insights and deployed on drill pipe and coiled tubing respectively, were developed to overcome these challenges. Three cases are presented in this paper: 1) optimize plug & abandonment (P&A) and slot recovery operations with smart intervention system in North Sea, 2) increase well life by employing intelligent coiled tubing enabled intervention services in Caspian Sea, and 3) Optimize re-entry stimulation with intelligent coiled tubing system in Middle East.
The intelligent intervention systems were proven to be critical and valuable to the success of above-mentioned intervention operations. For a P&A and slot recovery operation in an aging, deep and highly deviated well in North Sea, the drill pipe deployed smart intervention system was used in 4 different runs to deliver real-time insights to mitigate risks and ensure operational success. Equivalent Circulating Density (ECD), Weight on Bit (WOB) and torque readings increased confidence in making real-time decisions to respond to encountering total loss and obstruction during packer milling and wellbore cleanup operations. For the casing exit operation, real-time Casing Collar Locator (CCL) service enabled optimal whipstock placement, and WOB, torque and vibration data ensured a smooth and efficient casing window milling process, delivering a successful 7-in casing exit at 14,993-ft and 65 degree inclination. The intelligent coiled tubing system enabled an otherwise challenging and highly risky intervention operation to increase the life of a well in Caspian Sea. Uneven gravel packing in several sections allowed incoming sand to damage the screens and begin filling the wellbore. The intelligent coiled tubing intervention system not only assisted in setting a bridge plug at the depth of 13,481-ft, but was critical in enabling the setting of six expandable steel patches over two different intervals. Downhole readings, such as CCL, pressure, temperature, tension, compression and torque were critical to the success of the job. Total time to perform the entire operation was 286 hours with no Non Productive Time (NPT) and sand production was reduced significantly to an acceptable level. Finally, the intelligent coiled tubing system was employed in a rigless Thru-Tubing remedial stimulation operation in a horizontal well in Middle East to selectively target, isolate, and treat each Inflow Control Device (ICD) with an acid wash solution, re-establishing connectivity with the production zones. Real-time CCL helped to establish precise bottom hole Assembly (BHA) placement, and real-time parameter controls enabled more efficient system control and verification of inflatable element inflation and deflation. 13 successful Inflatable Straddle Acidizing Packer (ISAP) stages were achieved in a single coiled tubing (CT) trip and the total operation lasted only 21 hours, treating 11 intervals with flawless execution and zero no NPT.
The challenge of drilling through depleted zones, particularly in mature areas, continues to increase in importance as they are a frequent and familiar scenario for many fields. Pressure overbalances have been reported as high as 13,000 psi, although they more typically range in the hundreds to thousands psi. Wellbore stability problems associated with these zones can be linked to both drilling-induced and pre-existing fractures resulting in subsequent fluid losses. It is generally acknowledged that the solution to these problems is a combination of drilling fluid optimization and good drilling practices. Currently, the fluid solution is to incorporate large particulates in the form of a pill to seal such fractures, which consequently increases the drilling window. While the advantages of using a pill are known, large particulates also carry disadvantages, for example the retroactive nature of acting as a remedy rather than a prevention for lost circulation as well as leading to non-productive.
Formulations with various synergistic additives were examined through standard tests, including rheological profiles, high-pressure/ high-temperature fluid loss, and permeability plugging, some of which were performed on various porous disk media, including sandstone formation samples. Unique equipment was also developed and used to simulate a growing fracture mouth, or aperture, along with a proprietary mathematical model for the mechanism and geometry of fracture growth. The laboratory data supported a clear fracture mechanism and subsequent sealing, which was ultimately proven by yard test to confirm the laboratory and model predictions of performance.
Compared to commonly used particle packing/stress caging, the novel technology developed and testing performed demonstrates a new approach. The solution employs a continuous self-healing filtercake, rather than a large-sized lost circulation material pill application, to increase the drilling window and decrease risks of formation damage. The authors will present selected laboratory test methods and results, including a large scale fracture test and the associated mathematical modeling. This work shows a potential improvement in the drilling window while meeting environmental regulatory requirements in the Gulf of Mexico.
A critical design component on any steam injection project is to ensure steam containment. Loss of steam containment is not only a safety hazard, but also leads to poor well performance. Large changes in temperature have always been challenging to maintaining cement integrity not only during temperature ramp up, but certainly over the life of the well. Using high temperature swellable technology as part of the design for containment has proven to be highly effective.
In the design of a well, there are multiple casing strings, each with containment criteria and challenges. Challenges typically are due to difficulties in placing the cement and uncertainties on borehole shape. For years swellable packers have been used in conjunction with cement to overcome these challenges where cement alone has a low probability of providing successful containment. These challenges become more difficult in steam applications. Advancements in packer design and elastomer technology has led to the development of packers that can be run in casing designs which will encounter temperature up to 575°F (302°C). During the well design, critical containment areas are reviewed and consideration for the inclusion of a high temperature swellable packer is performed.
An operator of a cyclical steam injection project typically has seen steam at surface within days or weeks after initial heat up of the well. This results in additional steps to operate, maintain, and report on the well. High temperature swellable packers were piloted over a selected number of wells. It was found that wellhead pressure on cemented annuli was eliminated or significantly reduced after the first cycle of steam injection. The practice of including the packers now is used on every well and success is still being observed after multiple cycles of temperature. This reduces safety hazards as well as improve performance of the wells.
Goncalves, Kyle (The University of Texas at Austin) | Ashok, Pradeepkumar (The University of Texas at Austin) | Cavanaugh, Martin (Cavanaugh Consulting) | Macpherson, John (Baker Hughes) | Behounek, Michael (Taylor Thetford) | Nelson, Brian (Apache Corp)
Data exchanges between different electronic data recorder (EDR) systems and personnel occur on a regular basis in a well drilling operation. A significant portion of this data is derived; i.e., calculated or manipulated after sensor measurements. Currently, derived data calculations are poorly documented; therefore, the usefulness of this data diminishes through data transfer. The objective of this work is to define a meta-data framework for derived data.
In this paper, we focus our efforts on one derived data channel, the rate of penetration (ROP) and identify the meta-data required to fully understand the values transferred to the end user. We start by identifying the different types of ROP and document the calculation procedure for each type. Part of the meta-data that needs to be captured involves data transformations that occur when this data stream is moved from one EDR to the next. We interviewed various EDR providers in an attempt to understand their current process.
The different types of ROP calculations and their use in different types of drilling performance analysis are described in this paper. The calculation procedures were implemented and tested on an operator's data aggregation system. This effort also documents different EDR systems and how they handle sensed data required for ROP calculations. A meta-data framework is able to capture not just the calculation used, but also data transformations that occur as data hops from one EDR system to the next. Different data transfer protocols such as WITS0, WITSML, and OPC/UA necessitates a broad meta-data framework. While much of the meta-data can be embedded in the data transfer channel itself, a document describing all relevant meta-data is equally effective in communicating the information. Lastly, the meta-data framework developed here can also be applied to other forms of derived data (such as Hole depth, Bit Depth, WOB, etc.).
This meta-data framework improves the transparency by providing guidelines to data aggregation providers on the type of information that should be supplied to end users. It also provides insights into how data gets transformed from its point of origin (sensor) to its point of consumption. Finally, it also documents the various type of ROPs and their appropriateness for the analysis that is performed using them.
The objective of this work is to evaluate the efficacy of empirical models in forecasting oil production in shale reservoirs, bycomparing and analyzing their fit and effectiveness to our dataset. The following three modelswere considered: A Conventional Decline Curve Analysis (CDC), an Unconventional Rate Decline (URD) Approach, and a Logistics Growth Analysis (LGA) method. A comparative study is performed to evaluate the use of Artificial Neural Networks (ANN) for production forecasts and to reinforce the thinking that it is imperative to include physical parameters in mathematical models to predict accurateforecasts.
For this project, we used non-linear regression to fit empirical models to the dataset obtained from North Dakota Industrial Commission (NDIC). We evaluated the fit of modelswith the help of coefficient of determination. Physical parameters, such as porosity, saturation, shale volume, etc., and log data from sonic logs, gamma ray logs, etc., were selected as input to the ANN model andwere aided by Analysis of Variances (ANOVA).
Amongst the empirical models for shale play, URD method is the most commonly used since it is idealfor fractured reservoirs with extremely low permeability. URD model did fit the cumulative production profiles, but could not accurately fit the monthly production profile. The CRD approach was overallunsuccessful in generating accurate future production profiles. Values forecasted from the ANN show less than 10% error in estimation. The inclusion of physical parameters has proven to be extremely promising in the forecast production from fields that do not have sufficient history for statistical fitting.
Through aselection of physical properties from different sources, we have built an ANN model that fits with the production data in wells that have adiverse production history. Our work has shown the importance of including physical parameters into a process that was heretofore seen as a time series regression problem. In general, our new ANN-based method generated the best results.
For a stress-sensitive reservoir, the constant rock compressibility term used in a conventional reservoir simulator (CRS), does not account for change of porosity and permeability. This paper develops a coupled geomechanics and reservoir simulator (CGRS) which accounts for changes in porosity and permeability related to deformation.
The simulator in this paper adopts a staggered grid finite difference method for fluid flow and displacements. Displacements and pore pressures are placed at centers of faces and grid blocks, which increases numerical accuracy. Four types of nonlinear, coupled equations (porosity, permeability, displacements, and pressure equations) have been derived for use in CGRS. The Newton-Raphson method requires solving all the unknowns simultaneously, a computationally intensive procedure. An alternative is to use the Macro Gauss-Seidel method, which divides a huge nonlinear matrix into several smaller matrices, thus speeding up computations.
Solutions from CGRS have been validated using two analytical solutions: a one dimensional consolidated reservoir and an idealized reservoir. This validated simulator is used to simulate a 3D reservoir with multiple vertical and horizontal wells. The comparison between CRS and CGRS shows that pressure depletes faster in CRS as compared to CGRS. CGRS results in higher bottom-hole pressure for a constant rate well. Constant rate wells yield a result of 1 to 1.26 times higher bottom-hole pressure than CRS. This shows that neglecting geomechanics effects in CRS can lead to an under prediction of reservoir/bottom hole pressures and production rates. Another powerful function of CGRS is the output of 3D displacements, which cannot be predicted by CRS. After producing for 1000 days, the maximum vertical displacement reaches 0.34 ft. (0.085% of reservoir thickness). Maximum displacements in the x and y directions (lateral displacements) are 4 × 10-4 ft. and 0.015 ft., both of which are smaller than vertical displacement because of fixed lateral boundary conditions.
Unlike traditional iterative coupled (IC) methods, fluid flow and geomechanics share the same mesh, which solves the problem of numerical instability in two discretization methods used in traditional IC. Also, the change of volumetric strain with respect to time (usually neglected in traditional IC) has been included in the fluid flow equation to better characterize the effects of solids movement on fluid flow. The Macro Gauss-Seidel method was adopted to increase computation efficiency of the simulations. The simulator introduced in this paper has its own data structure for geomechanics analysis which can be incorporated in single-phase, two-phase, three-phase or compositional reservoir simulators.
Jiang, Tongwen (Tarim Oilfield Company, Petrochina) | Zhang, Hui (Tarim Oilfield Company, Petrochina) | Wang, Haiying (Tarim Oilfield Company, Petrochina) | Yin, Guoqing (Tarim Oilfield Company, Petrochina) | Yuan, Fang (Tarim Oilfield Company, Petrochina) | Wang, Zhimin (Tarim Oilfield Company, Petrochina)
The Kelasu gas field located in northern Tarim Basin had experienced four tectonic evolutions, with the most intense deformation between northern margin of the basin and southern Tianshan Mountains. A series of sandstone faulted anticline gas reservoirs were produced after the Himalayan movement. Faults were the main channel to transport natural gas from Jurassic coal-bearing formation to sandstone reservoir in Cretaceous. Simultaneously, the faults play a key role for fluid flow during the development of the gas field, but it is a huge challenge to evaluate the influence of faults on fluid flow quantitatively with depletion. To solve this problem, an integrated research combined geology, geomechanics and gas reservoir engineering was conducted. Firstly, 6 geological factors associated with connectivity and sealing properties of faults was analyzed to determine the critical factors among them. Secondly, based on 4D geomechanical modeling and 3D stress analysis of faults' plane, a calculation model of faults geomechanical activity index (FGAI) was built. Finally, the relationships between faults geomechanical activity and performance of gas field development were investigated to understand the influence of faults' mechanical behavior on production and water invasion during development in Kelasu gas field.
It is shown that faults geomechanical activity has profound influence on the performance of Kelasu gas field. 1.The faults geomechanical activity is one of key factors to control permeability, which can indicate the difference of permeability around faults and permeability variation during depletion. 2.With the depletion during exploitation the in-situ stress regime in Kelasu gas field changed from strike slip to normal faulting, and the heterogeneity was also gradually increasing which two resulted in the variety and complicate of faults' geomechanical activity. 3.It is found that there is a good correlation between the faults geomechanical activity and water invasion. The water breakthrough was early and gas-water interface rose fast near the faults with higher geomechanical activity index during depletion. 4.The complex relationship between stress field and faults system resulted in a great difference of faults geomechanical activity index in different location of reservoir. FGAI (Faults geomechanical activity index) is the highest in western reservoir, followed in turn by the eastern, northern, southern, so there is the most rapid uplift of gas-water interface in the western, followed in turn by other parts. Based on evaluation of faults geomechanical activity in this area, this reservoir could be divided into three blocks by different water invasion risk. Areas and gas wells with high risk water invasion were warned in advance. 6.For optimization of well placement, we found that FGAI is relatively low in northwestern reservoir, the fault sealing ability is high, the research provided one of basis for the placement of a new gas well.
A fault geomechanical activity index (FGAI) model for the gas reservoir with complex structure and high pore pressure and high in-situ stress was established. And its validity and effectiveness toward development of gas field was proved by production data and information. Based on the quantitative classification and description of faults geomechanical activity to investigate the influence of faults on water invasion, the mechanism of heterogeneous water production was determined in Kelasu gas field. The research provided the sealing evaluation of faults for new wells placement and risk prediction of water breakthrough for gas wells during depletion.
Most production wells currently drilled in the North Sea are in complex geological settings. In order to place the wells safely and effectively, drilling a successful production well requires an advanced technology and integrated proactive reservoir navigation approach, in addition to multiple data driven answer products from downhole tools.
Extra deep azimuthal resistivity logging while drilling (LWD) tools can detect boundaries up to 30 m away from the wellbore given optimal resistivity conditions. Combined with multicomponent inversion modelling (MCWD), the data acquired are used to map multiple boundaries, individual sand bodies, reservoir thicknesses, and lateral reservoir changes.
Borehole images aid in geosteering and are used to steer up or down based on structural boundaries identified on the image. Using wired pipe technology that provides telemetry rates good enough for memory-resolution data, the full resolution electrical image is available while drilling.
Despite complex reservoir geometry in both external boundaries and internal sedimentary structure, it was possible to succesfully geosteer by using an integrated geosteering approach. Through MCWD inversion, it was possible to track a thin, highly resistive layer at the roof for much of the reservoir, which allowed for proactive geosteering, optimizing wellbore placement and mapping of reservoir volumes.
Recovery mechanisms are more likely to be influenced by grid-block size and reservoir heterogeneity in Chemical EOR (CEOR) than in conventional Water Flood (WF) simulations. Grid upscaling based on single-phase flow is a common practice in WF simulation models, where simulation grids are coarsened to perform history matching and sensitivity analyses within affordable computational times. This coarse grid resolution (typically about 100 ft.) could be sufficient in WF, however, it usually fails to capture key physical mechanisms in CEOR. In addition to increased numerical dispersion in coarse models, these models tend to artificially increase the level of mixing between the fluids and may not have enough resolution to capture different length scales of geological features to which EOR processes can be highly sensitive. As a result of which, coarse models usually overestimate the sweep efficiency, and underestimate the displacement efficiency. Grid refinement (simple downscaling) can resolve artificial mixing but appropriately re-creating the fine-scale heterogeneity, without degrading the history-match conducted on the coarse-scale, remains a challenge. Because of the difference in recovery mechanisms involved in CEOR, such as miscibility and thermodynamic phase split, the impact of grid downscaling on CEOR simulations is not well understood.
In this work, we introduce a geostatistical downscaling method conditioned to tracer data to refine a coarse history-matched WF model. This downscaling process is necessary for CEOR simulations when the original (fine) earth model is not available or when major disconnects occur between the original earth model and the history-matched coarse WF model. The proposed downscaling method is a process of refining the coarse grid, and populating the relevant properties in the newly created finer grid cells. The method considers the values of rock properties in the coarse grid as hard data, and the corresponding variograms and property distributions as soft data. The method honors the fluid material balance and geological features from the coarse model. A workflow is outlined to address uncertainties in geological properties that can be reduced by integrating dynamic data such as sweep efficiency from interwell tracers. We provide several test cases and demonstrate the applicability of the proposed method to improve the history-match of a chemical EOR pilot. Further, we evaluate the fitness of different heterogeneity measures for grid-ranking of CEOR processes.