The Integrated Technology of Residual Reserves Localization and Profit Increase on Brownfields

Brown fields that are currently experiencing production decline can benefit a lot from production enhancement operations based on localization of residual reserves and geology clarification. The set of solutions includes targeted recommendations for additional well surveys followed by producers and injectors workovers, like whole wellbore or selective stimulation, polymer flow conformance, hydraulic fracturing and side tracking. As a result, previously poorly drained areas are involved in production, which increases current rates and ultimate recovery. The integrated technology of residual reserves localization and production increase includes: Primary analysis of the production history for reservoir blocks ranking by production increase potential. Advanced bottom-hole pressures and production history analysis by multiwell deconvolution for pressure maintenance system optimization and production enhancement. Advanced production logging for flow profile and production layer-by-layer allocation. Conducting pulse-code interference testing for average saturation between wells estimation. 3D reservoir dynamic model calibration on advanced tests findings. Multi-scenario development planning for the scenario with biggest NPV regarding surface infrastructure. The presented integrated technology is carried stage by stage. Based on the data analysis at the first stage (the Prime analysis) it is possible to get three types of results. The top-level assessment of the current development opportunities of the area, evaluation of current residual reserves on base of displacement sweep efficiency estimation, and evaluation of the potential production increase for various blocks of the field. Results of the second stage were obtained for the block deemed with the highest potential for production increase. Those results may reveal possible complications, and relevant workovers can be advised along with additional surveys that can further help to locate current reserves. The last stage of Prime analysis provides the most suitable choice was to perform an advanced logging and well-testing, as they include both single-well and multi-well tests. Pulse-code interference tests, multi-well retrospective tests and reservoir-oriented production logging make it possible to scan the reservoir laterally and vertically, which is especially important for multi-layered fields. The reservoir parameters obtained from the test results are used to calibrate the dynamic reservoir model. The effects of production enhancement operations are calculated from the 3D model. The set of possible activities is evaluated in terms of their financial efficiency based on the economic model of the operator company using multi-scenario approach on a specifically created digital twin of the field. The unique feature of this approach lies in an integrated usage of advanced production history analysis, advanced logging and well-testing technologies, as well as further calibration of the dynamic reservoir model based on test results and used-friendly interface for field digital twin interaction. This paper demonstrates on how to use the field tests results to calibrate the reservoir model and increase the accuracy of production forecasting by reducing the model uncertainty, with intent to increase profit of brownfields.

Well Connectivity Analysis with Deep Learning

Knowledge of well connectivity in a reservoir is crucial, especially for early-stage field development and water injection management. However, traditional interference tests can often take several weeks or even longer depending on the distance between wells and the hydraulic diffusivity of the reservoir. Therefore, instead of physically shutting in production wells, we can take advantage of deep learning methods to perform virtual interference tests. In this study, we first used the historical field data to train the deep learning model, a modified Long- and Short-term Time-series network (LSTNet). This model combines the Convolution Neural Network (CNN) to extract short-term local dependency patterns, the Recurrent Neural Network (RNN) to discover long-term patterns for time series trends, and a traditional autoregressive model to alleviate the scale insensitive problem. To address the time-lag issue in signal propagation, we employed a skip-recurrent structure that extends the existing RNN structure by connecting a current state with a previous state when the flow rate signal from an adjacent well starts to impact the observation well. In addition, we found that wells connected to the same manifold usually have similar liquid production patterns, which can lead to false causation of subsurface pressure communication. Thus we enhanced the model performance by using external feature differences to remove the surface connection in the data, thereby reducing input similarity. This enhancement can also amplify the weak signal and thus distinguish input signals. To examine the deep learning model, we used the datasets generated from Norne Field with two different geological settings: sealing and nonsealing cases. The production wells are placed at two sides of the fault to test the false-negative prediction. With these improvements and with parameter tuning, the modified LSTNet model could successfully indicate the well connectivity for the nonsealing cases and reveal the sealing structures in the sealing cases based on the historical data. The deep learning method we employed in this work can predict well pressure without using hand-crafted features, which are usually formed based on flow patterns and geological settings. Thus, this method should be applicable to general cases and more intuitive. Furthermore, this virtual interference test with a deep learning framework can avoid production loss.

Putting the Reservoir to Test: An Innovative Multi-Zone Drill Stem Test Method Revealed Critical Reservoir Characteristics, Horizontal and Vertical Connectivity for Field Development Decisions and Reserve Calculations

Information from dual-zone drill-stem tests (DSTs) and vertical interference tests, especially between oil and water zones, is very valuable for reservoir characterization under dynamic conditions. Despite the critical information that can be gathered for field development decisions, it is also an uncommon test type at a DST scale because of the advanced downhole test string design and operational complexity. This paper describes the objective-driven test design for a multi-layered carbonate reservoir and how the test sequence was modified in real-time to increase the value of information. An unconventional multi-zone well test with flexible on-demand control functionality was executed to resolve vital reservoir uncertainties for field development, including vertical interference between zones, individual zone characteristics and to confirm reservoir boundaries. Reservoir simulations were performed to decide the test sequence to create interference between different reservoir layers, while considering other test objectives, simultaneously. A DST string with wirelessly-activated downhole tools and flexible control options allowed to modify the test program on the fly, based on real-time data analysis and performance of each zone. One of the zones was also tested and characterized without flowing fluids to surface by making use of real-time downhole data. This complex, unorthodox well test operation was chosen to resolve multiple reservoir uncertainties in a single DST run, which would have normally required multiple different DSTs. Operations included flowing different zones individually, including acidizing operations, and the sequence was monitored and modified on the fly to maximize the value of data. Vertical interference between oil and water zones were also monitored to determine test conditions. Reservoir simulation studies helped choose the optimum test sequence to create the required interference by avoiding any disturbance in the interference data from other pressure transients during the test. During the test, downhole and surface testing data was transmitted to town in real-time and analyzed by the petro-technical team to guide the operational procedures. Downhole equipment was controlled wirelessly by acoustic commands to change the test design, depending on the data analysis. This thick carbonate formation was tested pre- and post-acid, to evaluate stimulation efficiency. Also, by testing the well at different flowrate and pressure conditions, information regarding future production well behavior was obtained. A low-pressure water zone was also tested without bringing fluids to surface, using a type of closed chamber test which was made possible by analyzing real-time downhole data from different depths. Multiple crucial objectives for field development decisions were planned and successfully obtained using an engineered DST string design. The confirmed reliability of complex DST string and wireless telemetry in difficult environment enabled well test efficiency gains to solve multiple challenging dynamic reservoir evaluation problems, simultaneously. These novel solutions bring new types of data and information to the exploration and appraisal teams to answer connectivity questions in a cost and time effective manner.

Well Interference Detection from Long-Term Pressure Data Using Machine Learning and Multiresolution Analysis

Knowledge of reservoir heterogeneity and connectivity is fundamental for reservoir management. Methods such as interference tests or tracers have been developed to obtain that knowledge from dynamic data. However, detecting well connectivity using interference tests requires long periods of time with a stable reservoir pressure and constant flow-rate conditions. Conversely, the long duration and high frequency of well production data have high value for detecting connectivity if noise, abrupt changes in flow-rate and missing data are dealt with. In this work, a methodology to detect interference from longterm pressure and flow-rate data was developed using multiresolution analysis in combination with machine learning algorithms. The methodology presents high accuracy and robustness to noise while requiring little to no data preprocessing. The methodology builds on previous work using the Maximal Overlap Wavelet Transform (MODWT) to analyze long-term pressure data. The new approach uses the ability of the MODWT to capture, synthesize and discriminate the relevant reservoir response for each individual well at different time scales while still honoring the relevant flow-physics. By first applying the MODWT to the flow rate history, a machine learning algorithm was used to estimate the pressure response of each well as it would be in isolation. Interference can be detected by comparing the output of the machine learning model with the unprocessed pressure data. A set of machine learning, and deep learning algorithms were tested including Kernel Ridge Regression, Lasso Regression and Recurrent Neural Networks. The machine learning models were able to detect interference at different distances even with the presence of high noise and missing data. The results were validated by comparing the machine learning output with the theoretical pressure response of wells in isolation. Additionally, it was proved that applying the MODWT multiresolution analysis to pressure and flow-rate data creates a set of "virtual wells" that still follow the diffusion equation and allow for a simplified analysis. By using production data, the proposed methodology allows for the detection of interference effects without the need of a stabilized pressure field. This allows for a significant cost reduction and no operational overhead because the detection does not require well shut-ins and it can be done regardless of operation opportunities or project objectives. Additionally, the long-term nature of production data can detect connectivity even at long distances even in the presence of noise and incomplete data.

A Brief Introduction in the Mitigation of Conducted Electromagnetic Interference lssues

This paper deals with the mitigation of the influence of electromagnetic conducted emissions in low voltage grids, which can be performed using different filtering methods. Due to the relatively young age of the electromagnetic compatibility domain, the specific terminology is not yet fully consecrated. That is why the specific literature abounds in a bunch of definitions and notions, incomplete, redundant, or worse, even contradictory. Therefore, all over this paper, the terminology from the successive issues of the standard IEC 60050-161 International Electrotechnical Vocabulary, is used. The introductory section presents generalities regarding the broader context of electromagnetic compatibility in which the paper fit. Section II is devoted to measurement techniques and measuring equipment used in conducted electromagnetic interference tests, specifically for electromagnetic emissions that flow in/from the equipment under test through power lines in the standardized frequency range from 100 kHz to 30 MHz. These measurement techniques and equipment are further used in the next section which presents electromagnetic interference experiments, performed on an induction motor driven by a frequency converter. To mitigate the conducted electromagnetic emissions to fit into the standard limits, a cascade of two EMI filtering cells has been designed and implemented. This demonstrated the usefulness and effectiveness of mains EMI filters in low voltage power applications. The experiment also demonstrated that in some cases it would be necessary to retrofit more than one filtering cell

The Use of Quantum Dot Inflow Tracers in Multi-Well Reservoir Production Surveillance and Inter-Well Diagnostics

Reservoir pressure maintenance is an extremely important factor in field development. In enhanced oil recovery water flooding projects, it is essential to optimize the flooding efficiency in a timely manner and reduce uncertainties in inter-well hydrodynamic modelling. Usually, the inter-well space parameters are assessed using interference tests or tracer- based surveillance. These methods offer such advantages as reliable information on the flow communication in the target area and the reservoir connectivity in different zones of the field. However, the duration and cost of the described surveillance technologies pose a significant drawback, and therefore alternative physical and mathematical methods with simplified forecast models are widely spread. This paper describes a method for integrating the results of dynamic marker-based inflow production surveillance in horizontal wells and the Spearman's rank-order correlation method. This approach is applied to provide better interventions for reservoir pressure maintenance, optimization of in-fill drilling, update existing hydro-dynamic models and reduce the level of uncertainty in decision making.

Fluid Migration Characterization of Full-scale Annulus Cement Sections Using Pressure-Pulse-Decay Measurements

Fluid migration behind casings is a well integrity problem that can result in sustained casing pressure, undetected leaks to the environment and potentially very challenging remediation attempts. Understanding the geometric dimensions and extent of annular migration paths is important for diagnosing and effectively treating fluid migration and sustained casing pressure problems in wells. We report measurements of permeability and micro-annuli in two full-scale cemented annulus test sections using a combination of transient pressure-pulse-decay and steady state seepage measurements. One of these sections is a cemented 9 5/8-in and 13 3/8-in casing section from a 30 years old Norwegian North Sea production well. For both sections we find equivalent micro-annulus sizes that are within the range of effective wellbore permeabilities based on sustained casing pressure records and previous vertical interference tests in wells. The test sections display measurable axial permeability variations with the bottom part of these vertical sections having the lower permeability. For the retrieved casing section the change corresponds to the transition through the top of cement which is nearly in the middle of the test section. Increasing internal casing pressure is found to slightly reduce the equivalent micro-annulus size, indicative of fracture-like response of the migration paths. A perceived benefit of the transient test procedure discussed herein is a significantly faster permeability characterization especially within low-permeable sections where it is otherwise difficult to establish steady state flow conditions.

Fourier Transform Infrared (FTIR) Spectroscopy for Measurements of Vehicle Exhaust Emissions: A Review

Pollution from vehicles is a serious concern for the environment and human health. Vehicle emission regulations worldwide have limits for pollutants such as hydrocarbons, CO, and NOx. The measurements are typically conducted at engine dynamometers (heavy-duty engines) sampling from the tailpipe or at chassis dynamometers (light-duty vehicles) sampling from the dilution tunnel. The latest regulations focused on the actual emissions of the vehicles on the road. Greenhouse gases (GHG) (such as CO2, CH4, N2O), and NH3 have also been the subject of some regulations. One instrument that can measure many gaseous compounds simultaneously is the Fourier transform infrared (FTIR) spectrometer. In this review the studies that assessed FTIRs since the 1980s are summarized. Studies with calibration gases or vehicle exhaust gas in comparison with well-established techniques were included. The main conclusion is that FTIRs, even when used at the tailpipe and not at the dilution tunnel, provide comparable results with other well-established techniques for CO2, CO, NOx, while for hydrocarbons, higher deviations were noticed. The introduction of FTIRs in the regulation needs a careful description of the technical requirements, especially interference tests. Although the limited results of prototype portable FTIRs for on-road measurement are promising, their performance at the wide range of environmental conditions (temperature, pressure, vibrations) needs further studies.

Innovative Use of Injectivity Tests as Interference Tests during Field Development: The EGINA Experience

This paper presents the innovative use of interference tests in the assessment of reservoir connectivity and the field oil production rate during the development phase and prior to the first oil of the EGINA field, which is located in a water depth of 1600 m, deep offshore Niger Delta. The interference test campaign involved 26 pre-first oil wells (13 oil producers and 13 water injectors) to assess and subsequently mitigate reservoir connectivity uncertainties arising from the numerous faults and between the different channels within the complexes. The results proved valuable in confirming or otherwise reservoir connectivity, field oil production rate and the number of wells required at first oil to achieve the production plateau. The tests were designed using the analytical method (PIE software) and the reservoir simulation models enabling to establish the cumulative water injection required, the injection duration and the time a response is expected at the observers. These all had impacts on the planning, OIMR vessel requirements and selection of permanent downhole gauges for the wells. In addition, the tests were performed with the water injectors as pulsers and the oil producers as observers allowing to avoid and the associated environmental impact. Ten interference tests were realized compared to four planned in the FDP partly due to the use of the more cost effective OIMR vessel in addition to the rig.

Interpretation of pressure interference tests for wells connected by a large hydraulic fracture

Shale formations are being exploited in several places around the world. Thus, an adequate characterization of such formations is recommended. In this work, two interpretation methodologies—TDS technique and conventional analysis—are implemented for determining the fracture permeability, from interference tests, between two wells connected by a large hydraulic fracture. Therefore, equations have been developed for both interpretation techniques and tested with synthetic examples. The estimated fracture permeabilities closely match the values initially used for the simulation of the tests.