Introduction

Long-distance horizontal well drilling technology and large-scale volume fracturing technology are widely used, which have effectively promoted the exploration and development of unconventional oil and gas reservoirs. Pattern infill has become a major way of improving the development effect in unconventional reservoirs. With the development of unconventional reservoirs expanded, pattern infill is extensively employed (Miller et al. 2016). For example, more than 70% of wells drilled in 2017 are infill wells in the Eagle Ford shale reservoirs (Lindsay et al. 2018). Large-scale volume fracturing measure is often required due to the complicated pore structure, limited permeability, and considerable heterogeneity of unconventional reservoirs. When the space between infill wells and old wells is too small during the process of hydraulic fracturing, the danger of fracturing interference increases and the production performance of interference wells may change. If the well spacing is too large, the unfractured region between infill wells and old wells will be extensive, and the reserve of this region will be unable to produce, which results in poor development performance. As a result, it is necessary to assess the degree of fracturing interference during large-scale volume fracturing of wells, which can optimize the distance of infill wells and old wells of unconventional reservoirs.

Currently, the degree of fracturing interference is mostly represented in the degree of inter-well connectivity between new wells and old wells. The degree of fracturing interference is mostly estimated by assessing inter-well connectivity in fractured well groups. There are several ways for assessing the inter-well connectivity of fractured well groups, which include microseismic monitoring, interference testing, tracer monitoring, and production dynamic analysis (Maxwell et al. 2009; Han et al. 2019; Raterman et al. 2019; Wang et al. 2020). The key to microseismic monitoring technology is the inversion and position of microseismic events, which can only describe the range of fracturing fractures and is difficult to represent the real geometry of fracturing cracks. As a result, microseismic monitoring data can’t be used to accurately assess inter-well connectivity (Maxwell et al. 2009). To improve the accuracy of evaluation results, some researchers combine other data to develop a method. Based on tracer monitoring results in the Ma 131 area of Mahu Oilfield, Liu analyzes the rule of the minimum distance between microseismic event points and adjacent good event points without the influence of natural fractures and forms an interwell connectivity evaluation method for fractured wells in glutenite reservoirs (Liu et al. 2022). Guindon explains the communication types of fractures during hydraulic fracturing using comprehensive production dynamic data and microseismic monitoring data (Guindon 2015). The evaluation method for inter-well connectivity based on microseismic monitoring data can achieve a qualitative description of inter-well connectivity, but it can’t quantitatively determine the degree of inter-well connectivity. At the same time, the microseismic monitoring process is complex and costly (Liu et al. 2022). In terms of interference well testing, the simulated production cycle can be divided into full cycle models, linear flow models, and elliptical flow models (Aissa and Youcef 2003; Apte and Lee 2017; Gao et al. 2020). The full-cycle models comprise analytical, semi-analytical, discrete numerical methods based on the point source function, linear flow models and elliptical flow models are based on analytical methods (Aissa and Youcef 2003; Apte and Lee 2017; Gao et al. 2020). Yu et al. (2016) proposes an interpretation model of well interference with complex fracture conditions and solves it using semi-analytical methods. Unstructured grids are utilized to mimic well interference between multi-stage fracturing horizontal wells in unconventional reservoirs (Siddiqui and Kumar 2016). Marongiu-Porcu uses a discrete fracture model coupling with a fracture growth model to develop a numerical model of inter-well interference in shale reservoirs (Marongiu et al. 2016). Iino et al. (2020) employs the streamlined numerical simulation technology to create a numerical simulation multi-well model, which takes into account inter-well interference in unconventional reservoirs and discusses the influence of inter-well interference using streamlined analysis. Because of the complexity of formation after large-scale volume fracturing in unconventional reservoirs, there is a significant difference between the theoretical model and actual reservoirs, which limits the application of interference test results (Kasumov et al. 2019; Uzun et al. 2019). Tracer monitoring technology is used to evaluate the fracturing effect and inter-well connection, which needs to inject a tiny quantity of tracer directly into fracturing fluid during hydraulic fracturing and monitor its backflow. It is commonly used to assess the inter-well connectivity of fractured horizontal wells in unconventional reservoirs (Mulkern et al. 2010; Leong et al. 2015; Kumar and Sharma, 2018). King and Leonard (2011) present an analytical approach for evaluating fracture characteristics and inter-well connectivity using tracer monitoring technology, which is validated by actual well-monitoring data. Sani et al. (2015) examines the interwell connectivity of fractured horizontal wells in the Haynesville shale gas reservoir using more than 5 months of tracer flowback data. It shows that the closer the non-chain fracturing wells are, the stronger the connectivity is, but the pressure barrier effect causes the fractures of two wells to shift during the chain fracturing process. Shen et al. (2021) develops an element tracer and applies it in the Fuling Shale Gas Field, evaluates the connectivity between wells in the good group JY66, and verifies that the element tracer technology is simple and effective for inter-well connectivity evaluation of shale gas reservoirs. Torrealbo et al. (2017) uses a tracer to characterize reservoir heterogeneity, which improves the accuracy of inter-well connectivity characterization. Due to the difficulties of laboratory analysis, the cost of tracer monitoring is enormous (Shen et al. 2021). Simultaneously, the interpretation model is based on the ideal formation, and the results need further verification (Kumar et al. 2020). Based on production performance analysis to evaluate fracturing interference, relevant scholars have summarized the relevant interference laws based on production performance data of adjacent wells after hydraulic fracturing (Kurtoglu and Salman 2015; Xu et al. 2023; Cui et al. 2022; Liao et al. 2022). Malpani et al. (2015) classifies the impact of fracturing interference into positive or negative based on the production performance of adjacent wells. In positive impact, the production improves after fracturing interference, while fracturing interference can lead to permanent or temporary production loss during negative impact. Miller et al. (2016) investigates about 3100 fracturing interference events in the five major basins of the United States and finds that fracturing interference has a more positive impact on production for Haynesville and Bakken shale reservoirs, but most fracturing interference hurts production in Woodford and Niobrara shale reservoirs. Although production performance analysis can determine the inter-well connectivity, it can only be qualitative and cannot be quantitative. Because of the special completion technology of wells and the change in fracturing flow capacity, the phenomenon of inter-well interference is a dynamic change, which makes evaluating inter-well interference difficult (Uzun et al. 2019).

Although these technologies for monitoring inter-well connectivity are diverse, their applications are complex and costly. During the fracturing process of some unconventional reservoirs, engineers monitored the wellhead pressure of adjacent wells to analyze the degree of inter-well connectivity (Rimedio et al. 2015). Based on the variation characteristics of wellhead pressure, fracturing interference can be classified into three forms based on the fluctuation features of the pressure curve during the fracturing process: fracturing shadow interference, crushing interference, and numerous interference mechanisms (Pankaj 2018). This paper proposes a new approach to evaluating fracturing interference between new and old wells, which is based on a systematic analysis of the variation pattern of old well wellhead fracturing during the fracturing process of new wells. This method quantitatively provides the degree of interference between various fractures and old wells during the hydraulic fracturing process, as well as the degree of interference between new wells and old wells within a well group. Based on the wellhead pressure and the production performance data of well group A of the Fuling shale gas field, the analysis process and results of this new approach are explained. This result has a certain guiding significance for the infill well pattern design and fracturing scale design of the Jiaoshiba shale reservoir.

Overview of monitoring the well group

Well, group A is a production well group in the Fuling shale gas field. Fuling shale gas field is located in Chongqing, southwest China, and it is a mountainous-hilly landform that structurally corresponds to the Wanxian synclinorium in the eastern Sichuan Basin's high-steep fold belt (Mu et al. 2011). The Upper Ordovician Wufeng Formation-Lower Silurian Longmaxi Formation is the major development layer of the gas field, which is a deep-water shelf sedimentary environment with a thickness of 85–135 m. The lithology is primarily gray-black siliceous shale, which may be split into ①-⑨ strata vertically from bottom to top. The Table 1 shows the stratigraphic parameters of each stratum. The most promising lithofacies for shale development are the carbon-rich and high-silicon shale facies in the layers ①-⑤. Except for the layer ⑥⑦, the porosity increases little from bottom to top, the rest are larger than 4%. Gas saturation steadily drops from bottom to top. According to preliminary experiments and geological research results of this reservoir, the classify limit of U content is 45 ppm, TOC content is 2%, and Quartz content is 40%. (Table 1)

Table 1 Stratigraphic parameter table of each small layer
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The well group-A is one of the production platforms in the Fuling shale gas reservoir, which contains old wells (A7-1, A7-2, A7-3, A15-2, A15-3) and new wells (A68-S2 and A68-5). The relationship between the plane positions of each well in well group A is shown in Fig. 1. Each well is completed using long-distance horizontal wells and large-scale volume fracturing technology, and its production layers and fracturing parameters are shown in Table2.

Fig. 1
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Location diagram of the well group A

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Table 2 Completion parameter table of each well
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Fracturing interference monitoring technology and interpretation method

Fracturing interference monitoring technology

With large-scale volume fracturing technology and pattern infill technology used in the development of unconventional reservoirs, the phenomenon of fracturing interference between new and old wells is widespread. Some monitoring technologies have been developed to determine the fracturing interference phenomenon between wells, and wellhead pressure monitoring technology is one of them. Due to the change in the formation stress field or the influence of inter-well connectivity, the wellhead pressure of old wells will generally rise to a certain extent during the fracturing process of new wells, which reflects the fracturing interference of new wells on old wells. Fracturing interference can be classified into three forms based on the fluctuation features of the pressure curve during the fracturing process: fracturing shadow interference, crushing interference, and numerous interference mechanisms (Pankaj 2018). There is no direct fracture contact between the new well and the old well when the fracturing shadow interference happens. Wellhead pressure in old wells continues to climb steadily based on the fracturing stress field. The monitoring well's pressure curve exhibits modest pressure increase characteristics (Fig. 2a). When crushing interference occurs, hydraulic fractures become directly linked between two wells, which causes the wellhead pressure of monitoring well to rapidly increase (Fig. 2b). When numerous interference mechanisms function at the same time, the pressure varies in the monitoring well, and the pressure curve exhibits cyclic fluctuation features (Fig. 2c). Crushing interference and fracturing shadow interference are two common types of fracturing interference, which are caused by different interference mechanisms. Crushing interference and fracturing shadow interference are to some extent independent, but sometimes they can affect each other. If there is fracturing shadow interference during fracturing, the propagation path of fracture will be affected by the formation stress field, which results in a change in the direction of crack propagation and affects the response characteristics of fracturing interference. According to the above theory, the wellhead pressure change of old wells can be monitored during the new well's fracturing process, and the type and size of fracturing interference can be determined by the wellhead pressure curve.

Fig. 2
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Pressure curve during the different types of fracturing interference (Pankaj 2018)

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Interpretation method of fracturing interference monitoring data

Based on monitoring data of fracturing well construction pump pressure and wellhead pressure during the hydraulic fracturing, the pressure curves of monitoring wells are drawn (Fig. 3). The scatter points represent the wellhead pump pressure of the fracturing well (new well) during each construction period, and the spacing between the scattered points represents the period that well is closed after each stage of fracturing. The continuous pressure curve represents the wellhead pressure of the monitoring well (old well). The variation of wellhead pressure can reflect the degree of fracturing interference between new and old wells during hydraulic fracturing.

Fig. 3
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Pressure curves of new and old wells

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(1) Method for determining the degree of fracturing interference between old wells and fracturing sections.

If the pressure rise value of the monitoring well is Δpui during the i-th stage of hydraulic fracturing of the infill, the upward pressure rise of the monitoring well during the entire hydraulic fracturing process can be expressed as:

$$\Delta p_{u} = \sum\limits_{i = 1}^{n} {\Delta p_{{{\text{ui}}}} }$$
(1)

If the pressure drop value of the monitoring well isΔpdi during the i-th stage hydraulic fracturing of the infill well, the pressure drop value of the monitoring well during the entire fracturing process can be expressed as:

$$\Delta p_{d} = \sum\limits_{i = 1}^{n} {\Delta p_{{{\text{di}}}} }$$
(2)

Since strong fracturing interference occurs during the fracturing process, the wellhead pressure of the monitoring well will significantly increase. When the fracturing interference is weak, the wellhead pressure rises little. As a result, The magnitude of pressure changes at the wellhead of the monitoring well can reflect the degree of interference between hydraulic fractures and monitoring wells. The fracturing interference degree of each fracturing section on monitoring well can be expressed as:

$$w_{{{\text{ui}}}} = \frac{{\Delta p_{{{\text{ui}}}} }}{{\sum\limits_{i = 1}^{n} {\Delta p_{{{\text{ui}}}} } }}$$
(3)

During the hydraulic fracturing process, the pressure drop of the monitoring well is influenced by various factors such as the type of fracturing interference and formation permeability, which cannot fully reflect the degree of fracturing interference. Since the pressure drop can also reflect the connectivity between two wells to a certain extent, it can be used to verify the accuracy of calculation results based on the interference level of each fracturing section.

(2) Evaluation method for the degree of fracturing interference between monitoring well and fracturing well.

During the development of unconventional reservoirs with a three-dimensional well network, hydraulic fracturing of infill wells can cause interference to some wells of the well group. Assuming there is a total of m wells in the well group, wellhead pressure variation of the j-th well during hydraulic fracturing of infill wells can be expressed as:

$$\Delta p_{j} = \sum\limits_{i = 1}^{n} {\Delta p_{j,i} }$$
(4)

The pressure rise value of all monitoring wells can be stated as:

$$\Delta p = \sum\limits_{j = 1}^{m} {\sum\limits_{i = 1}^{n} {\Delta p_{j,i} } }$$
(5)

The magnitude of upward pressure in monitoring wells reflects the degree of interference of infill wells on monitoring wells. The greater the upward pressure of monitoring well, the greater the degree of interference. The pressure rise value of the monitoring well is small, and the degree of interference is small. Taking these monitoring wells as a whole, the interference degree of infill well on monitoring well j can be expressed as:

$$\eta_{j} = \frac{{\Delta p_{j} }}{{\sum\limits_{j = 1}^{m} {\Delta p_{j} } }}$$
(6)

Analysis and evaluation of fracturing interference in the well group A

In well group-A, wells A7-1, A7-2, A7-3, A15-2, and A15-3 are existing old wells. The infill wells A68-5 and A68-S2 were completed in November 2019 with horizontal lengths of 2099 m and 1805 m, respectively. Large-scale volume fracturing is adopted in the infill wells A68-5 and A68-S2. The pressure curves are produced by monitoring wells A7-1, A7-2, A7-3, A15-2, and A15-3 during the hydraulic fracturing of infill wells (Fig. 4). The pressure rises of wells A7-2 and A15-2 in the wells group-A are greater, and the well A15-2 is very minor. During the fracturing process of a new well, the changes in the wellhead pressure of the old well are influenced by various factors. In well group A, the relative position relationship between new wells and old wells has a certain impact on the pressure response of old wells. The closer the position is, the more obvious the response is.

Fig. 4
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Pressure curves of infill wells and monitoring wells

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Using the fracturing construction time of infill well A68-5 as each fracturing section, the wellhead pressure rise of monitoring wells is counted (Tables 3 and 4). The cumulative pressure change value of well A7-1 increases by 4.15 MPa during the hydraulic fracturing process, and the pressure rise is more noticeable during the hydraulic fracturing process of 2-nd, 14-th and 13-th fracture stages, which are 23.77%, 18.39%, and 16.68%, respectively. It indicates that the 2nd, 14th, and 13th fractures of the infill well have a strong fracturing interference on the well A7-1. The total pressure change of well A7-2 increases by 20.25 MPa. The pressure rise is more visible during the fracturing process of the 1-st, 2-nd, 3-rd, 4-th, and 6-th stages, and the proportion of pressure rise is larger than 10%. This shows that these fractures interfere with the well A7-2 significantly. The cumulative pressure rise of well A7-3 increases by 3.25 MPa, and the pressure increases significantly during the 1st and 2-nd stages of fracturing. This indicates that these fracture stages have a strong degree of fracturing interference with the well A7-3. The pressure of well A15-2 increases by 6.62 MPa, and the pressure rise is particularly noticeable during the fracturing of the 17th section, with a pressure rise ratio of 67.02%. It shows that the fracture stage interferes strongly with the well A15-2. The cumulative pressure rise of well A15-3 increases by 3.24 MPa, and the pressure increases significantly during the fracturing process of Sects. 13-th, 14-th, 15-th, and 16-th, with a pressure increase ratio of over 10%. This indicates that the above fracture sections have a strong degree of interference with the well A15-3.

Table 3 Statistical results of pressure rise in each monitoring well during each fracturing section of the A68-5 well
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Table 4 The percentage of upward pressure increase in each monitoring well during the fracturing of each section of Well A68-5
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In well group-A, the cumulative pressure rise of these monitoring wells increases by 37.52 MPa during the hydraulic fracturing process of infill wells A68-5 and A68-S2 (Fig. 5). The pressure change value of well A7-2 is 20.25 MPa, which accounts for 53.97% of the pressure increase value of well group-A. It indicates that the connectivity between well A7-2 and infills wells is the best in the well group-A, and is most strongly affected by fracturing interference. The well A15-2 is the second with a pressure increase of 6.62 MPa. The wells A7-3 and A15-3 have the smallest impact of fracturing interference, with upward pressure increases of 3.26 MPa and 3.24 MPa, accounting for 8.68% and 8.64%, respectively. This indicates that the connectivity between these two wells and infill wells is poor, and the impact of fracturing interference is the weakest.

Fig. 5
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Pressure response value and percentage of each well in the well group-A

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This method only needs to monitor wellhead pressure during the hydraulic fracturing process to calculate the connectivity between old wells and new wells. At the same time, It can also provide the magnitude of fracturing interference between each fracturing crack and old wells. Compared with tracer monitoring and inter-well interference testing, This method has low cost and is easy to apply.

Verification and discussion of interpretation results

Based on production data from unconventional reservoirs, Miller et al. summarize the production changes of old wells after fracturing interference and introduce the calculation method of old well production before and after fracturing interference (Miller et al. 2016). It points out that the impact of fracturing interference on the production of old wells can be divided into three categories: positive impact, negative impact, and no impact. Pankaj (2018) determines the degree of fracturing interference and calculates the production change law of old wells under different types of fracturing interference using a numerical simulation method based on the pressure response characteristics of old wells. It is found that the production of old wells varies greatly when there is obvious fracturing interference. Therefore, the accuracy of inter-well connectivity can be verified by analyzing the changes in the production performance curves of old wells before and after fracturing interference. By analyzing the production performance of old wells before and after fracturing interference, it is found that the production of well A7-2 increases significantly after hydraulic fracturing, and the average daily production of 3 months increases from 3.6 × 104 to 4.88 × 104 m3/d, an increase of 35.18% (Fig. 6). The wells A15-2 and A7-3 declines by 18.63% and 14.25%, respectively. The well A7-1 rises 13.96%. The well A15-3 has the least effect, rising by 1.07% (Fig. 7 and Fig. 8). The results are essentially compatible with the pressure response characteristics of old wells, which shows that it is feasible to use wellhead pressure monitoring to evaluate the degree of fracturing interference.

Fig. 6
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Production curve of A7-2 well in 3 months before and after hydraulic fracturing

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Fig. 7
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Comparison of 3 months' average production of old wells before and after hydraulic fracturing in well group-A

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Fig. 8
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Comparison of average production change rate of old wells in 3 months before and after hydraulic fracturing in well group A

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The impact of fracturing interference on the production of old wells can be divided into three categories: positive impact, negative impact, and no impact. In well group A, the impact of fracturing interference on good production is mainly reflected in positive and no effects. This is mainly influenced by various factors such as reservoir physical properties and hydraulic fracturing scale, and the impact mechanism of fracturing interference on production still needs further analysis. Although the relevant mechanisms still need further research, it can be concluded that using the monitoring data of old well wellhead pressure can achieve a semi-quantitative evaluation of the interference degree of infill wells and old wells. Compared with the tracer monitoring method and the interference well testing method (Wang et al. 2020; Kasumov et al. 2019; Torrealba et al. 2017), this method is simpler in operation and has little impact on good production during the testing process. The analysis method is simple and practical, and it is suitable for oilfield applications.

conclusion

  1. (1)

    A monitoring method for evaluating the fracturing interference between new wells and old wells during the hydraulic fracturing process of infill wells has been proposed, which can achieve a preliminary evaluation of the connectivity between the new wells and old wells. This method is simpler and cheaper than tracer monitoring methods and interference testing methods, and it is suitable for oilfield applications.

  2. (2)

    Based on the wellhead pressure monitoring data of well group A, the method proposed in this paper is used to achieve the degree of interference between hydraulic fractures and old wells. This achieves a quantitative evaluation of the main fracturing stages that interfere with the old wells.

  3. (3)

    Based on the wellhead pressure monitoring data, this method is used to evaluate the inter-well connectivity of well group A. The analysis results are consistent with the results of dynamic data analysis, which verifies the feasibility of this method.