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Summary Offshore reservoirs are subjected to pressure loading from the ocean tide. The resulting pressure fluctuation, notably its amplitude and phase, provides valuable information regarding the formation compressibility and heterogeneity. The purpose of the present study is twofold: First, to propose a method for calculating tidal efficiency from harmonic analysis of regional tide stations and detrended bottomhole pressure (BHP), and second, to compare the compressibility from tidal analysis with that obtained from rock‐mechanics measurements and material balance. This case study is on a fractured oil field for which matrix laboratory measurements alone cannot capture the large‐scale formation compressibility that is driven by the fracture distribution. This paper will show how, in the absence of seabed‐pressure measurements, a synthetic diurnal tide can be simulated by interpolating the harmonic constituents of neighboring tide stations. The validity of this method was confirmed on two offshore fields. A new procedure that combines a Savitzky and Golay (1964) (SG) filter and cubic splines gave satisfactory results to filter out the tidal signal residual from the reservoir‐transient response for both buildup and interference tests. In addition, this paper found that wells in fractured areas of the field have higher rock compressibility and exhibit a higher tidal efficiency. The same effect is observed in flank wells with higher water saturation. Conversely, the tidal efficiency is dramatically reduced in wells experiencing gas breakthrough.
Summary Acid tunneling is an acid‐jetting method for stimulating carbonate reservoirs. Several case histories from around the world were presented in the past showing optimistic post‐stimulation production increases in openhole wells compared with conventional coiled‐tubing (CT) acid jetting, matrix acidizing, and acid fracturing. However, many questions about the actual tunnel creation and tunneling efficiency are still not answered. In this paper, the results of an innovative full‐scale research program involving water and acid jetting are reported for the first time. The tunnels are constructed through chemical reaction and mechanical erosion by pumping hydrochloric acid (HCl) through conventional CT and a bottomhole assembly (BHA) with jetting nozzles and two pressure‐activated bending joints that control the tunnel‐initiation directions. If the jetting speed is too high and the acid is not consumed in front of the BHA during the main tunneling process, then unspent acid flows toward the back of the BHA and creates main wellbore and tunnel enlargement with potential wormholes as fluid leaks off, lowering the tunneling‐length efficiency. Full‐scale water‐ and acid‐jetting tests were performed on Indiana limestone cores with 2‐ to 4‐md permeability and 12 to 14% porosity, sourced from the same supplier. Many field‐realistic combinations of nozzle sizes, jetting speeds, and casing pressures were included in the testing program. The cores were 3.75 in. in diameter × 6 in. in length for the water tests and 12 in. in diameter × 18 in. in length for the tests with 15‐wt% HCl acid. The jetting BHA was moved as the tunnels were constructed, at constant force on the nozzle mole, to minimize the nozzle standoff. Six acid tests were performed at the ambient temperature of 46°F and two at 97°F. The results from the acid tests show that the acid‐tunneling efficiency, defined as the tunnel length divided by the acid volume, can be optimized by reducing the nozzle size and pump rate. The results from the water and acid tests with exactly the same parameters to match the actual CT operations in the field show that the tunnels are constructed mostly by chemical reaction and not by mechanical erosion. The acid‐tunneling efficiencies obtained from the full‐scale acid tests are superior to the average tunneling efficiency of more than 500 actual tunnels constructed during more than 100 acid‐tunneling operations performed to date worldwide. Although the tunnel lengths and acid volumes for the actual tunnels constructed during the previous acid‐tunneling operations were recorded by the service company performing those operations, little downhole temperature and formation characterization data were provided by the operators to the service company. Thus, the downhole‐temperature and formation‐characterization effects on the acid‐tunneling efficiency for the previous field operations are unknown. In this paper, we describe the full‐scale water‐ and acid‐jetting tests on Indiana limestone cores. The major novelty of this test program consists of performing all measurements with casing pressure, unlike all previous water‐ and acid‐jetting studies performed at atmospheric conditions and reported in the literature, which is closer to the field conditions during CT operations. The novel understanding of the combined effect of the nozzle size, pump rate, and casing pressure significantly improves the actual acid‐tunneling efficiency.
Summary A successful rigless subsea stimulation was executed during 2018, with the intervention performed on three target wells offshore of Sabah Malaysia, at a water depth of approximately 1400 m (4,593 ft). Significant changes in reservoir performance prompted an acid‐stimulation and scale‐squeeze treatment, designed to remedy fines migration and scaling issues within the well and production system. Treatment fluids were delivered subsea by an open‐water hydraulic access system, using a hybrid coiled tubing downline (HCTD). Access to the subsea trees was enabled by a novel choke‐access technology, allowing for a flexible, cost-efficient, and low‐risk intervention. The intervention system was installed on a multiservice vessel, with the downline deployed via the vessel moonpool. A second support vessel was used as required to provide additional fluid capacity without disturbing primary intervention operations. This enhanced the flexibility of the operation, accommodating potential changes in the treatment plan without impact to critical path‐stimulation activities. The full intervention was delivered as an integrated service, with all elements supplied by a single provider, via one contract. An established network of in‐house equipment, expertise, test laboratories, and operational bases supported the planning and execution of the project. This was complemented by select external providers for vessels, remotely operated vehicle services, and other specialist contractors. The challenges faced during execution included completion of a comprehensive treatment fluid test program, importation and logistics of equipment from around the globe, and managing operational risks, all within a condensed timeline to satisfy a brief intervention window. A collaborative solution was developed that combined the resources of the service provider, inclusion of performance-based elements within the contract, and delivery of an efficient and flexible well-access technology that supported rapid mobilization and alleviated operational risk. Post‐stimulation well testing confirmed an average increase in oil productivity of 86%, with a corresponding productivity‐index factor gain of 3.4. These results confirm the appropriateness of open‐water hydraulic access using coiled tubing (CT) for performing cost‐effective stimulations on complex subsea wells.
Summary One of the considerations in out‐of‐sequence‐fracturing treatment is creating fracture complexity through reducing the in‐situ differential stress to enhance hydraulic‐fracture connectivity by activating natural fractures, fissures, faults, and cleats within the formation to create secondary or branch fractures (induced‐stress‐relief fractures) and connect them to the main biwing hydraulic fractures. In out‐of‐sequence fracturing, this is achieved by beginning fracturing Stage 1 at the toe of the well and then moving toward the heel and fracturing Stage 3 so that there is a degree of interference between the two fractures, followed by placing Stage 2 between the previously fractured Stages 1 and 3. Out‐of‐sequence fracturing in this mode ensures that the fracture in Stage 2 (center fracture) takes advantage of the altered stress in the rock and connects to the stress‐relief fractures from the previous Stages 1 and 3 (outside fractures), thus enhancing the connectivity of the fracture network. The first successful field trial of out‐of‐sequence fracturing was executed by Lukoil in treating eight wells in western Siberia in 2014. The first case of out‐of‐sequence fracturing in North America was later conducted in western Canada in 2017, with eight more trials followed in 2017, 2018, and 2019. In this work, a 3D hydraulic‐fracture‐extension simulator is rigorously calibrated by history matching the observed treatment pressures from the out‐of‐sequence‐fracturing field treatment in western Canada to reliably quantify the effective fracture geometries. Then, a separate set of fracture modeling is conducted to predict the hydraulic‐fracture geometries in a conventional (sequential‐fracturing) treatment of the same candidate well. Finally, production forecasting is used to assess the production potential from the candidate well according to each set of the generated fracture geometries from each of the scenarios (out‐of‐sequence fracturing vs. conventional sequential fracturing). The results of coupling the rigorously calibrated fracture modeling and production forecasting indicate noticeable production‐uplift potential from a carefully designed out‐of‐sequence‐fracturing vs. sequential‐fracturing treatment. Besides, the discovered characteristic trends in fracture geometries in out‐of‐sequence fracturing confirm some of the findings obtained in a previous sensitivity analysis of out‐of‐sequence fracturing. The previous sensitivity study entailed analyzing nearly 200 fracture‐modeling scenarios using a variety of geomechanical properties and treatment‐design variables. These characteristic trends render unique opportunities and advantages for the optimization of fracturing treatments and field development. This work is the first attempt in comparative evaluation of the effect of out‐of‐sequence fracturing by incorporating the actual field data into fracture modeling coupled with production forecasting. The learnings from this multifaceted study are worth sharing with the industry and could be used to guide future successful designs of the out‐of‐sequence fracturing for completion optimization in both unconventional and conventional reservoirs. From a large‐scale field‐development perspective, when conducted in multiple wells, optimized out‐of‐sequence fracturing has the potential of rendering full‐length interference effect and optimizing the stress shadowing while reducing the risk of well bashing.
Summary Engineers commonly expect symmetric fracture wings in multiple‐transverse‐fracture horizontal wells. Microseismic surveys have shown that asymmetric hydraulic fractures grow away from the recent fractured wells and grow toward previously produced wells. This might be caused by the elevated stress around the recently fractured well and the reduced stress near the depleted wells. This paper presents the asymmetric fracture growth observed by the microseismic events, develops a simple model to simulate the fracture propagation, and discusses its effect on the well productivity. Motivated by the microseismic observations, we developed a simple 2D fracture model to simulate asymmetric fracture wings that can capture the behavior of fracture hits between two adjacent horizontal fractured wells. Fluid leakoff during fracture propagation is considered in the model. The effect of asymmetric fractures on production is evaluated with numerical simulations. The newly developed fracture model shows that the fracture can grow asymmetrically if the horizontal well is near where the stress field is different between its two sides. Numerical simulation is used to quantify the productivity reduction caused by asymmetric hydraulic fractures. Our results provide a reason for why asymmetric fractures occur and demonstrate that they do penalize well performance. Our model suggests the importance of fracturing under a balanced‐stress distribution that benefits long‐term production. Use of this model also suggested that an optimized hydraulic‐fracturing‐treatment design will improve the overall performance of multiple parallel wells, which minimizes or avoids asymmetric fracture wings. The fracture‐propagation model and productivity model provide simple but profound guidelines for well‐pad management, including well spacing, stage planning and spacing, and completion and production order.
Summary The primary objectives of perforating a lengthy cased‐and‐cemented wellbore section for fracture stimulation are to enable extensive communication with the reservoir and control the allocation of fluid and proppant into multiple intervals as efficiently as possible during fracturing treatments. Simultaneously treating multiple intervals reduces the number of fracture stages required, thus reducing treatment cost. One way to control the allocation is to use limited‐entry perforating. Execution and optimization of limited‐entry perforating requires awareness of the factors that can affect performance. This paper presents a case study of plug‐and‐perforate horizontal‐well treatments in an unconventional shale play in which various diagnostic methods were used to better understand these factors. Within the case study, three types of perforation‐evaluation diagnostics were implemented: injection step‐down tests and pressure analysis of the fracturing treatments, video‐based perforation imaging, and distributed acoustic sensing (DAS). Injection step‐down tests indicated that all perforations were initially accepting fluid. Surface‐pressure analysis of the main fracturing treatments indicated that in certain cases, several perforations were not accepting fluid and proppant (slurry) by the end of the job. Video‐based imaging indicated that a large majority of perforations showed unambiguous evidence of significant proppant entry. Evaluation of the erosion patterns on the perforations showed a positional bias where for a given fracture stage, perforations in clusters nearest the heel of the well were more eroded than perforations in clusters nearest the toe of the well. DAS analysis showed a positional bias, allocating more slurry volume to clusters nearest the heel of the well. However, DAS analysis also showed that changing the number of perforations in a cluster had a larger effect than the positional bias. The results of the case study indicated that a staggered perforation design using more gradual changes among clusters would lead to a more balanced treatment. This scenario was evaluated along with a job design featuring high excess perforation friction and an equal number of perforations in each cluster. Fracture‐simulation runs indicated that both tactics are likely to improve slurry allocation.
Summary Knowledge of fracture‐entry pressures or formation‐face pressures (FFPs) during acid‐fracturing treatments in real‐time mode can help in evaluating the effectiveness of the treatment and improve the decision‐making process during execution. In this paper, methods and tools used to generate FFPs in real‐time mode with the help of bottomhole‐pressure (BHP) data are discussed in detail. The horizontal wells selected for the study were drilled and completed in the North Sea with permanent BHP gauges that enabled constant monitoring of downhole pressures. The tool in discussion uses the combination of treatment data such as surface pressure, fluid density, injection rates, fluid type, wellbore details, and wellbore deviation, along with bottomhole‐gauge pressures, to calculate fracture‐inlet pressures just outside the casing at active perforation(s) depth. The tool performs the calculations in “live” mode during treatment execution and simultaneously generates a dynamic array of data that assists in “on‐the‐fly” evaluation and the decision‐making process. Several acid‐fracture treatments were analyzed using the tool and led to important conclusions related to fracture‐propagation modes, acid‐exposure times, and the effectiveness of given acid types. The results had a direct influence on the modification of treatment designs and pump schedules to optimize treatment outcomes.
Summary Proper lateral and vertical well spacing is critical to efficiently develop unconventional reservoirs. Much research has focused on lateral well spacing, but little on vertical spacing, which is important and challenging for stacked‐bench plays such as the Permian Basin. Following the previous single‐well study (Xiong et al. 2018), we performed a seven‐well case study to optimize completion design and 3D well spacings, by integrating the latest complex‐fracture‐modeling and reservoir‐simulation technologies. Those seven wells are located at the same section but also are vertically placed in four different zones in the Wolfcamp Formation in the southern Midland Basin. With the latest modeling technologies, we first built a 3D geological and geomechanical model, and full wellbore fracture‐propagation model for these seven wells, and then calibrated the model with multistage‐fracturing pumping history of each well. The resulting model was then converted to an unstructured‐grid‐based reservoir‐simulation model, which was then calibrated with production history. On the basis of the local geomechanical characterization, as well as confidence in the capacity of the models from our previous study, we conducted experiments in fracturing modeling to study the impact of different completion design parameters on fracture propagation, including cluster spacing, fracturing‐fluid viscosity, pumping rate, and fluid and proppant intensities. With the statistical distributions of fracture length and height from different completion designs, we then optimized the completion design, and studied lateral and vertical well spacings. The results show the following. The resulting fracture length and height from multistage fracturing treatments are in log‐normal distribution, which provides great insights on the probability of well interference/fracture hits and drained/undrained reservoir volumes. Both fracture hits/well interference and drainage volume depend on the well spacings and corresponding well completion designs The hydraulic‐fracture length, height, and network complexity mainly depend on in‐situ stress, cluster spacing, cluster number per stage, and fluid and proppant intensity. For the Wolfcamp Formation in the southern Midland Basin, tighter cluster spacing with fewer perforation clusters per stage and high fluid and proppant intensity, might create larger fracture surface area, which will increase the initial production rate and the ultimate recovery. Therefore, we can reasonably model complicated fracture propagation and well performance with the latest modeling technologies, and optimize both lateral and vertical well spacings, and the corresponding completion design. The application of those technologies could help operators save significant time and costs on well‐completion and ‐spacing pilot projects and, thus, speed up field‐development decisions. In addition, we will demonstrate a novel workflow to perform this job.
Summary The success of water‐conformance operations often depends on clear identification of the water‐production mechanism. Such an assessment can be complicated significantly when formation damage is also occurring. Coiled tubing (CT) and distributed‐temperature sensing (DTS) were combined to overcome challenging conditions (high temperature, low injectivity, high deviation, long perforated intervals, and wellbore damage) to identify damaged oil zones and suspected water‐bearing zones in an onshore well in Japan. The subject well experienced unexpected contamination of oil‐based mud (OBM) and completion brine, which generated tight emulsions in the wellbore during the completion phase. Despite a thorough cleanout and perforations, severe damage was observed and mostly water was produced. With the presence of persistent damage in the wellbore preventing any logging‐tool use, DTS was selected as main diagnostic method, with the fiber optics being deployed with CT to ensure full coverage of the interval. Acquired temperature surveys were processed and matched with simulated profiles, which tested various scenarios of damage. Ultimately, results were used to drive the design of remedial actions. The following operational sequence was implemented: temperature‐baseline measurements (6 hours), brine bullheading through the CT/tubing annulus at 0.2 bbl/min (22 hours), and shut‐in (6 hours) for warmback. The long injection stage was required to ensure that enough fluid was being injected across the entire interval while keeping the downhole pressure at less than the fracturing pressure. Real‐time DTS data during pumping and warmback indicated the presence of a main intake zone in the middle of the interval. Below that section, only marginal temperature changes were observed, which might be a direct consequence of the low‐injection‐rate limitation. Post‐job processing using numerical temperature simulation was performed to complement that analysis and quantify intake along the well. Temperature inversion against the DTS response was conducted independently using two different simulators, both of which yielded similar profiles, confirming the soundness of this approach. The results supported the presence of a larger intake in the middle interval and also showed that the bottom zone most likely took some fluid. Complementary information eventually pointed to the larger‐intake interval being the primary water‐bearing zone. This analysis led to the selection of the remedial actions to be performed in damaged oil zones. This study demonstrates how integrated use of data from design to job execution to interpretation can change the perception of a well and how DTS can be a viable alternative to damage and water‐production diagnostics in some extreme conditions when production‐logging tools (PLTs) cannot be used. Results of the DTS quantitative analysis provided local damage profiles along the well, which were critical to the subsequent planning of remedial activities.
Summary Predicting oilfield performance is extremely challenging because of the large number of variables that can influence and control it. Traditional methods such as decline‐curve analysis have been commonly used but have been shown to have significant shortcomings. In recent years, advances in machine learning (ML) have provided a new suite of tools to tackle complex multivariant problems such as understanding oil‐reservoir performance and predicating the final recovery factor. In this study, the application of a random‐forest algorithm to train three predictive models and investigate the influence of the various input variables was investigated. To train the algorithm, a database was built that includes information on 32 variables from 93 reservoirs from the Norwegian Continental Shelf. These variables control or potentially influence field performance and include factors that are a function of geology, subsurface conditions, fluids, and the engineering decisions taken in field development. In addition to these controlling parameters, data were also recorded for the fields that record performance. These included information on the estimated recovery factor and production rates. Eighty percent of the data were input into the random‐forest algorithm to train the models, whereas 20% were retained to blind test the subsequent models. Model accuracy was measured by comparing actual and predicted observations for each prediction metric using an R score, mean square error, and root mean square error. The production‐rate model had a mean square error of 0.004, whereas the mean square error for recovery factor was 0.024. Estimates of average monthly depletion rate have a mean square error of 0.0104. Predictor importance estimates indicate that geology/depth‐dependent variables such as stratigraphic heterogeneity, reservoir depth of burial, average porosity, and diagenetic impact are among the variables with high importance in predicting recovery factor. When predicting reservoir‐oil rate, the most important variables are related to field size, such as cumulative oil produced, number of wells, oil in place (OIP), and bulk rock volume. In this study, we provide data‐driven insight into understanding the relationship between subsurface and engineering conditions of reservoir producibility; we also provide a tool for predicating reservoir performance within a basin or region.