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During the development and production of oil fields, a large number of specialized oil equipment is required and utilized, and these devices account for a significant proportion of a company’s fixed assets. The equipment investment plan is an important part of a company’s production and operation plans. Selecting major petroleum equipment appropriately and making sound decisions regarding equipment investment are crucial for the sustainable development of a company. I. Establishment of the investment evaluation index system 1. Technical indicators of equipment The main technical indicators of equipment include lifespan, advancement level, compatibility, and standardization. 2. Economic indicators of equipment (1) Equipment investment payback period The equipment investment payback period refers to the time required to repay the principal amount of the equipment investment using all the net additional earnings generated by the equipment, either in one lump sum or over time; interest on the unpaid (or unrecovered) investment is then paid annually until the investment is fully repaid (or recovered). The payback period is used to evaluate the economic viability of an investment or the operational performance after the investment. Obviously, the shorter the payback period, the better. (2) Financial Net Present Value: The financial net present value refers to the sum of the present values of the net cash flows for each year within the project’s life cycle, discounted to the beginning of the construction period using either the industry’s benchmark rate of return or a specified discount rate (ic, when no benchmark rate of return is established). It is a dynamic evaluation indicator for assessing profitability during the accounting period. 3. Productivity indicators of equipment (1) Equipment capacity utilization Rate of capacity utilization refers to the extent to which the maximum possible capacity of the equipment is utilized. It can generally be considered from two aspects. First, it considers the operating hours of the equipment, that is, it evaluates the utilization level of the equipment by comparing its actual operating time with the available operating time ； Secondly, it is considered from the perspective of the equipment’s efficiency, that is, by examining the ratio of the actual amount of product processing (or workload) completed by the equipment per unit of time to the maximum amount of product processing (or workload) that the equipment can complete per unit of time, in order to assess its utilization level. To comprehensively reflect the above two aspects, the ratio of the annual expected amount of product processing (or workload) that the equipment can handle to its maximum annual capacity for product processing (or workload) is used to indicate the level of utilization of the equipment’s capacity. That is: In the formula, K represents the capacity utilization rate, Q1 is the estimated annual amount of product processing (or workload) that can be completed by the equipment, and Q2 is the maximum annual amount of product processing (or workload) that the equipment can handle. (2) Urgency of production needs: The requirements of production are the primary criterion for purchasing equipment. If production has a low demand for the purchased equipment, it inevitably leads to idleness and waste of that equipment. 4. Safety and environmental protection indicators of the equipment refer to the safety and environmental friendliness of the equipment. 5. Technical support indicators for the equipment mainly include three aspects: personnel training related to the equipment, supply of spare parts for the equipment, and maintenance service centers for the equipment. II. Establishment of a comprehensive investment evaluation model 1. Fuzzy evaluation method The fuzzy evaluation method is a technique that uses the set theory of fuzzy mathematics to conduct a comprehensive evaluation of a certain object. In real life, it is often difficult to accurately describe the object of evaluation; in such cases, the evaluation criteria are usually determined subjectively by decision-makers, which introduces uncertainty and a certain degree of ambiguity. (1) Determine the set of evaluation factors. The set of factors is a general collection of various elements that influence the object under evaluation. The factor set, also known as the set of evaluation indicators, is generally denoted as U={u1, u2, …, un}. The factors identified in this paper that influence equipment selection are as follows: U1={u11, u12, u13, u14}={Lifetime, Advancedness, Compatibility, Standardization}; U2={u21, u22}={Equipment Investment Payback Period, Net Financial Present Value}; U3={u31, u32}={Equipment Utilization Rate, Urgency of Production Needs}; U4={u41, u42}={Safety, Environmental Friendliness}; U5={u51, u52, u53}={Staff Training, Spare Parts Supply, Maintenance Facilities}. (2) Determining the rating scale for evaluation: The ratings for the evaluation indicators refer to the classification of the indicators at the highest level. Several experts can be invited to assess and assign ratings, which are generally divided into four levels: excellent, good, fair, and poor. We record the ratio of the four grades assessed by the experts (for example, if 10 out of 20 experts consider the indicator to be excellent, then the ratio is 1/2), which serves as important data for fuzzy judgment. A level set is generally denoted as V={v1, v2, … vn}. In this paper, the evaluation set V={v1, v2, v3, v4}={Excellent, Good, Fair, Poor} is formed by ranking from high to low. (3) Determining the judgment matrix: The evaluation objects are assessed based on the i-th factor Ui in the set of factors. If the degree of membership of the j-th element vj in the evaluation set is rij, then the result of the assessment using the i-th factor Ui can be represented by R. R is referred to as the set of factor evaluations; it is a fuzzy subset of the evaluation set V, and can be simply expressed as: Ri={ri1, ri2, …… rin}. Similarly, the single-factor evaluation sets corresponding to each factor are as follows: R1 (r11, r12, …… r1n), R2 (r21, r22, …… r2n), …… Rm (rm1, rm2, …… rmn). Since equipment evaluation involves numerous factors and complex relationships, it is difficult to determine the rij values accurately and reasonably using common fuzzy distribution functions; therefore, expert judgment is usually employed to determine these rij values. The specific steps are as follows: ① Design an expert evaluation form ； ②Please ask the relevant experts to evaluate the equipment plan based on their own judgment. It should be noted that the participants in the evaluation and assessment should be representative, so as to make the evaluation results more scientific. ③The evaluation forms filled out by each evaluator were compiled and entered into Table 1. A matrix composed of the membership degrees of each single-factor evaluation set as rows is called the unit-factor evaluation matrix. Obviously, R is a fuzzy matrix. (4) Fuzzy comprehensive evaluation model: Fuzzy comprehensive evaluation takes into account the influence of various factors to arrive at a correct judgment. That is, the Zadeh rule is applied for fuzzy multiplication, and then a comprehensive evaluation conclusion is drawn based on the \"principle of maximum membership.\" Its calculation formula is as follows: where bj refers to the fuzzy comprehensive evaluation index ； A is the weight set, with a1, a2, …, am being the weights of the 1st, 2nd, …, mth indicators respectively; R is the fuzzy evaluation matrix, and rij represents the degree of membership of the i-th indicator for the j-th evaluation level. Based on the degree of membership provided by bj, it is determined to which evaluation grade the evaluated object belongs, in order to assess its quality. 2. Comprehensive scoring method: When clear evaluation criteria are established for each assessment indicator, scores for those indicators of a particular device are assigned based on those criteria. At this point, the total score is calculated using the following formula: Where S represents the total score of the device, Si is the score for the i-th indicator, wi is the weight of the i-th indicator, with ∑wi=1, and m is the number of indicators. Based on the total score, it is possible to directly determine the quality of the evaluated subject. If the highest possible total score for the subject under evaluation is 10 points, it can be rated according to the following criteria: 9–10 points (including 9): Excellent; 7.5–9 points (including 7.5): Good; 6–7.5 points (including 6): Fair; less than 6 points: Poor. If the highest possible total score is not 10 points, it should be converted to a 10-point scale before rating it using the above criteria. 3. Determining indicator weights using the Analytic Hierarchy Process: The Analytic Hierarchy Process involves analyzing the factors contained within a complex system and their interrelationships, breaking down the system into various components, and classifying these components into different levels, thereby creating an objective multi-level analytical structure model. Each element at a given level is compared pairwise with an element from the level above it, in order to determine a scale for their relative importance; this process results in the creation of a decision matrix. By calculating the largest eigenvalue of the judgment matrix and its corresponding eigenvector, the order of importance of elements at each level relative to a certain element at a higher level is determined, thereby establishing a vector of relative weights. Finally, from top to bottom, the combined weights of the elements from the upper level are used as weights to weight and sum the relative weights of the elements at the current level, thereby determining the combined weights of the elements at each level with respect to the system’s overall goal. (1) Establish a hierarchical structure based on the overall objectives, as shown in Table 1. Table 1 List of Comprehensive Evaluation Index System for Equipment (2) Apply the comparative scale method to construct the comparative judgment matrix A = (aij) n×n for each level of factors. (3) Calculate the largest eigenvalue of the comparative judgment matrix and its corresponding eigenvector, and conduct a consistency check to obtain the weights of each factor at a certain level relative to the factors at the level above it. The methods for using the root method to find the largest eigenvalue of the comparison matrix A = (aij) n×n, as well as the method for determining the largest eigenvector (weight vector) and the consistency check, are as follows: ① Calculate the product of the elements in each row of the matrix. ② Calculate the nth root of Mi. ③ Normalize it; where Wi is the i-th component of the desired eigenvector (weight vector). ④To calculate the maximum eigenvalue λmax and the average random consistency index RI, Table 2 can be referred to: Table 2 Values of RI for Different Orders. ⑤ Consistency Check: Deviation consistency index, Random consistency ratio. If CR < 0.1, it can be considered that the judgment matrix has satisfactory consistency; otherwise, the elements in the judgment matrix must be adjusted again until satisfactory consistency is achieved. III. Application of comprehensive evaluation methods: When selecting equipment for investment, conducting a scientific comprehensive evaluation of such equipment is based on a reasonable set of evaluation indicators and appropriate evaluation methods. The indicator system is established based on the principles for its creation, as well as taking into account the factors reflected by each indicator in the equipment management process. The fuzzy comprehensive evaluation method is adopted for the evaluation approach; the Analytic Hierarchy Process is used to determine the weights of the indicator factors, and expert consultation is employed to assess these factors. Finally, evaluation conclusions such as “excellent, good, medium, poor” for the investment plan are drawn.