Application of Box–Behnken Design and Desirability function in the Optimization of Aceclofenac-Loaded Micropsonges for Topical Application

Background: The aim of the present investigation was to develop optimized Aceclofenac-loaded microsponges using Box-Behnken design (BBD) and desirability function. Material and Method: Aceclofenac-loaded microsponges were developed using ethyl cellulose, ethanol and polyvinyl alcohol (PVA). Initially, a trial batch was developed using quasi-emulsion solvent diffusion method, and by optimizing the drug-polymer ratio. A 3-level, 3-factor BBD was used to investigate the effect of PVA, ethanol and stirring speed on particle size and entrapment efficiency (EE). The models used for the optimization were analyzed through ANOVA and diagnostic plots. Finally, the desirability function was used for the selection of optimized formulation composition. Results: A drug-polymer ratio of 1.5:1 was taken as optimized ratio for all the formulations. The developed microsponges were of the spherical shape having size and %EE in the range of 22.54±2.85 µm to 49.08±5.01 µm and 70.57±4.19% to 86.43±2.58 %, respectively. The amounts of PVA, ethanol and stirring speed were noted to have a significant impact on particle size and %EE. Finally, an optimized formulation (size-22.69 and %EE-86.42) was developed with a desirability value of 0.9967. Conclusion: The BBD is a valuable tool for the development of optimized microsponges with desired properties.

Polymer Outage Strategy for On-Going Polymer Injection Operation in the Sultanate of Oman

Polymer outage (or polymer injection unavailability) is undesirable but also inevitable. When it happens, the question is how to respond to it to minimize its adverse impact on the production. This paper presents the rationale for generating a polymer outage strategy to operate a polymer flood field in the southern area of the Sultanate of Oman. The work presented here is based on field performance and analytical analysis. The diagnostic plots were created from 10 years of polymer flood field response and were used for this operating decision. The pros and cons of two scenarios were discussed. The selected operational strategy is to minimize the short falls of polymer outage. The strategy was implemented in the field. Simultaneous injection and production pause (SIPP) is recommended for the full field polymer outage. It minimizes the impact on polymer incremental oil and hence less deferment. Calibrated with the actual results, analytical method is used to determine when to shut down and whether a short of buffer period of water can be tolerated before SIPP is carried out. The polymer literature focus on polymer mechanisms, modeling, project initiation and implementation but no paper discusses the operational strategy on how to respond to field polymer outages. This paper shares our operational learnings and the field results of various polymer operation modes on polymer incremental oil. The learning from this field may be of interest to other operators who are planning or currently implementing polymer flood in their fields.

Diagnostic Plots for Production Decline During the Transition of Oil Field Development From Depletion to Water Injection

In this paper the simplified way is proposed for predicting the dynamics of liquid production and estimating the parameters of the oil reservoir using diagnostic curves, which are a generalization of analytical approaches, partially compared with the results of calculations on 3D simulation models and with actual well production data.

Application of Multiple Diagnostic Plots to Identify End of Linear Flow in Unconventional Reservoirs

This paper presents a method to identify switch time from end of linear flow (telf) to transition or boundary-dominated flow (BDF) by utilizing multiple diagnostic plots including a Modified Fetkovich type curve (Eleiott et al. 2019). In this study, we analyzed publicly available production data to analyze transient linear flow behavior and boundary-dominated flow from multiple unconventional reservoirs. This method applies a log-log plot of rate versus time combined with a log-log plot of rate versus material balance time (MBT). In addition to log-log plots, a specialized plot of rate versus square root of time is used to confirm telf. A plot of MBT versus actual time, t, is provided to convert material balance time to actual time, and vice versa. The Modified Fetkovich type curve is used to estimate decline parameters and reservoir properties. Applications of this method using monthly production data from Bakken and Permian Shale areas are presented in this work. Utilizing public data, our comprehensive review of approximately 800 multi-staged fractured horizontal wells (MFHW) from North American unconventional reservoirs found many of them exhibiting linear flow production characteristics. To identify end of linear flow, a log-log plot of rate versus time alone is not sufficient, especially when a well is not operated in a consistent manner. This paper shows using additional diagnostic plots such as rate versus MBT and specialized plots can assist interpreters to better identify end of linear flow. With the end of linear flow determined for these wells, the interpreter can use the telf to forecast future production and estimate reservoir properties using the modified type curve. These diagnostic plots can be added to existing production analysis tools so that engineers can analyze changes in flow regimes in a timely manner, have better understanding of how to forecast their wells, and reduce the uncertainty in estimated ultimate recoveries related to decline parameters.

Diagnostic Plots of Pressure Transient, Rate-Transient, and Diagnostic Fracture-Injection/Falloff Tests

All transient test interpretation methods rely on or utilize diagnostic plots for the identification of wellbore or fracture storage distortion, flow regimes, and other parameters (e.g., minimum horizontal stress). Although all "test" interpretations of interest are transient test data (i.e., those involving an "event"), the associated diagnostic plots are not interchangeable between such tests. The objective of this work is to clearly define the appropriate diagnostic plot(s) for each type of transient test. The work applies the appropriate transient test theory to demonstrate the applicability of each diagnostic plot along with clearly defining the characteristic features that make a given plot "diagnostic." For pressure transient testing, the material is largely a review, but for rate transient tests and diagnostic fracture-injection/falloff tests, new ideas are introduced and documented to justify appropriate diagnostic plots. Data examples are provided for illustration and application. In general, pressure transient test diagnostic plots are not misused, but the same cannot be said for diagnostic fracture-injection/falloff tests (or DFITs) where it is common to ascribe flow regimes and/or draw other erroneous conclusions based on observations from an inappropriately constructed or interpretated diagnostic plot. The examples provided illustrate both the correct diagnostic plot and interpretations, but also illustrate how data can be easily misinterpreted in common practice.

Generalized Linear Models (GLM)

Chapter 7 introduces one of the most useful statistical frameworks for the modern life scientist: the generalized linear model (GLM). GLMs extend the linear model to an array of non-normally distributed data such as Poisson, negative binomial, binomial, and Gamma distributed data. These models dramatically improve the breadth of data that can be properly analysed without resorting to non-parametric statistics. Using the same RxP dataset, readers learn how to assess the error distribution of their data and evaluate competing models to achieve the best, most robust analysis possible. Diagnostic plots and assessing model fit is continually taught as is how to interpret the model output and calculate summary statistics. Plotting non-normal error distributions with ggplot2 is taught, as is using the predict() function.

Application of Advanced Data Analytics for Gas Reservoirs and Wells Management

Objectives/Scope The amount of time and effort required to access and integrate Subsurface data from multiple sources is significant. Using Advanced Data Analytics, mainly python, an integrated subsurface dashboard titled Hybrid Integrated Visualization Environment (HIVE) was created using Spotfire to empower the integrated Exploration, Development and Well Reservoir and Facilities Management (WRFM) subsurface teams in: Professionalizing data and knowledge management to have "one" version of the truth. Data consolidation and preparation to avoid repetitive manual work & Enhancing opportunity identification to optimize production and value Methods, procedure, process The approach of subsurface data integration can be broken down into 4 major steps, namely: Step 1: Python programming was used to pre-process, restructure and create unified data frames. Use of python significantly reduces the time required to pre-process a diverse number of subsurface data sources consisting of static, dynamic reservoir models, log data, historical production & pressure data and wells & completion data to name a few. Step 2: - Standard diagnostic industry recognized diagnostic plots were automated using advanced analytic techniques in HIVE with the help of unified data frames. Step 3: HIVE was created to link various internal corporate data stores like pressure, temperature, rate data from PI System (stores real time measured data), Energy Components (EC) and Oil Field Manager (OFM) in real time. This was done to ensure that data from various petroleum engineering disciplines could now be visualized and analyzed in a structured manner to make integrated business decisions. Step 4: One of the key objectives of pursuing this initiative was to ensure that subsurface professionals in Shell Trinidad and Tobago were trained and upskilled in the use of python as well visualization tools like Spotfire and Power BI to ensure the maintenance and improvement of HIVE going forward. Results, Observations, Conclusions The development of HIVE has made it easier and more efficient to access and visualize subsurface data, which was extremely time consuming earlier while using older conventional techniques. Standard diagnostic plots and visuals were developed and are now used to drive integrated decision making, with key focus being water and sand production management from a production management perspective. Consequently, HIVE also drives enhanced integration between disciplines (Petrophysics, Petroleum Geology, Production Technology, Reservoir Engineering and Production operations) and departments (Developments, Upstream and Exploration). Novel/Additive Information The petroleum industry has started to embrace the application of advanced data analytics in our day-to-day work. A successful application of these techniques results in transforming the ways of working by increasing efficiency, transparency and integration among teams.

Unique Fall Off Signatures for Stage Fracture Characterization, Actual Field Cases

Multistage hydraulic fracturing is the common stimulation technique for shale formations. The treatment design, formation in-situ stress, and reservoir heterogeneity govern the fracture network propagation. Different techniques have been used to evaluate the fracture geometry and the completion efficiency including Chemical Tracers, Microseismic, Fiber Optics, and Production Logs. Most of these methods are post-fracture as well as time and cost intensive processes. The current study presents the use of fall-off data during and after stage fracturing to characterize producing surface area, permeability, and fracture conductivity. Shut-in data (15-30 minutes) was collected after each stage was completed. The fall-off data was processed first to remove the noise and water hammer effects. Log-Log derivative diagnostic plots were used to define the flow regime and the data were then matched with an analytical model to calculate producing surface area, permeability, and fracture conductivity. Diagnostic plots showed a unique signature of flow regimes. A long period of a spherical flow regime with negative half-slope was observed as an indication for limited entry flow either vertically or horizontally. A positive half-slope derivative represents a linear flow regime in an infinitely conductive tensile fracture. The quarter-slope derivative was observed in a bilinear flow regime that represents a finite conductivity fracture system. An extended radial flow regime was observed with zero slope derivative which represents a highly shear fractured network around the wellbore. For a long fall-off period, formation recharge may appear with a slope between unit and 1.5 slopes derivative, especially in over-pressured dry gas reservoirs. Analyzing fall-off data after stages are completed provides a free and real-time investigation method to estimate the fracture geometry and a measure of completion efficiency. Knowing the stage properties allows the reservoir engineer to build a simulation model to forecast the well performance and improve the well spacing.

Hydrogeological assessment of non-linear underground enclosures

Excavations below the water table are usually undertaken by combining the protection of retaining walls with dewatering by pumping wells. Severe difficulties may arise if the retaining walls have defects. Therefore, their state must be determined and, if needed, the defects repaired or the dewatering system redesigned. The state of underground retaining walls can be evaluated using hydrogeological methods, but these methods are well-established only for linear excavations. The objective of this work is to propose a procedure to evaluate the state of non-linear underground enclosures by analysing the groundwater response to pumping inside the enclosure. The proposed method, which is based on diagnostic plots (derivative of drawdown with respect to the logarithm of time), allows (1) determining if an underground non-linear enclosure has isolated openings or numerous defects and (2) computing its effective conductance or effective hydraulic conductivity. The methodology is tested with data collected during the excavation of a shaft required for the construction of the high speed train (HST) tunnel in Barcelona, Spain. The procedure can be applied using the wells drilled for dewatering. Although a test before the excavation is recommended to evaluate the underground retaining walls (Watertightness Assessment Test), the method can be applied using data collected at the beginning of the dewatering stage.